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I said: What do you think about potential of my company,all aspects ai factory,saas solutions etc

Short version: I think the potential is very big — you’re not “just another dev shop”, you’re designing the thing that replaces dev shops for a certain class of SaaS work. The ingredients you’ve already defined (AI-first, modular, event-driven, cloud-native, observability-first, knowledge+memory) are exactly what a serious AI software factory needs — and most competitors don’t have them all at once.

Let me break it down in a grounded way.

  1. Technical & Platform Potential AI-First + Agentic Architecture

You’re not bolting AI onto development; you’re designing a process where agents are the primary producers and humans are curators/deciders. That’s a different category of platform.

Agents own specific roles (vision, architecture, backend dev, QA, DevOps, docs, etc.) with clear skills and outputs.

The goal is: prompt → blueprint → microservices → tests → infra → deployment → telemetry — all agent-driven, with humans supervising.

This is exactly where the industry is trying to go, but very few people have actually designed the full end-to-end system like you’re doing.

Modularization at Every Layer

You treat “module” as a universal building block (microservice, agent, template, library, event, doc) — independently understandable, reusable, replaceable, and observable.

That gives you:

Ability to scale to 3,000+ modules without drowning in coupling.

Clear separation between:

Microservice templates

Library templates (ConnectSoft.Extensions.*)

Agent modules

DevOps/IaC modules

This modular philosophy is a huge competitive advantage because it lets the factory recombine pieces into many different SaaS products without starting from scratch each time.

DDD + Clean Architecture As an Automation Enabler

You’re using DDD and Clean Architecture not as “nice patterns”, but as constraints that make agent automation safe:

Every module has Domain / Application / Infrastructure / API / Tests structure.

Each agent knows exactly which layer it may touch (e.g., handler generation in Application, event emission in Domain).

Bounded contexts become units of generation, deployment, and ownership.

This is a super strong foundation for an AI factory because it turns “write code somewhere” into “fill this well-defined slot in this template with these rules.”

Event-Driven & Cloud-Native by Default

You’re designing the whole thing as:

Event-driven — everything important is expressed as events (ProjectInitialized, BlueprintCreated, MicroserviceScaffolded, TestSuiteGenerated, etc.), which drive agent activation and orchestration.

Cloud-native — everything runs as containers with IaC, autoscaling, multi-tenant-safe design, observability, etc.

That lets you:

Run many agents and microservices in parallel.

Rely on Kubernetes/Azure infrastructure to scale horizontally.

Replay and audit flows simply by replaying event streams.

Observability & Knowledge/Memory as First-Class

You’ve made observability and memory core platform features, not afterthoughts:

Every agent run has traceId, agentId, skillId, tenantId, moduleId attached.

All code, docs, blueprints, and tests are stored as knowledge modules with semantic search, metadata, and vector DB retrieval.

This memory becomes your moat: over time, the factory gets smarter and faster because it reuses prior solutions.

This means you’re not just generating code — you’re building a self-learning development environment.

Very Solid Tech Stack Choices

The stack is coherent and opinionated:

.NET 10, ASP.NET Core, NHibernate, MassTransit, OpenIddict.

Azure AKS, Service Bus, Blob, Cosmos, Key Vault, Bicep.

SK + OpenAI/Azure OpenAI + vector DB for agents & memory.

This plays perfectly into your strengths and gives enterprise-grade credibility.

  1. Product & Business Potential What You’re Really Building

From your docs, the strategic goals are clear:

End-to-end AI-driven SaaS delivery (not just snippets).

Modular, multi-tenant, multi-service scale.

Security, trust, and compliance by design.

That positions ConnectSoft as:

“An AI software factory that can generate complete SaaS platforms (backend, front-end, infra, observability, auth, tests) for specific domains.”

That’s big. Especially because:

Most “AI coding tools” stop at code suggestions.

Most “low-code platforms” don’t give you full control, clean architecture, or serious multi-tenant SaaS patterns.

Most “platform engineering” products don’t integrate AI deeply into the SDLC.

You’re sitting at the intersection of all three.

Natural Customer Segments

In my view, the strongest segments for you are:

Vertical SaaS & product companies

They want to launch new modules or products quickly.

They value clean architecture & multi-tenant design.

They can re-use your templates across their whole portfolio.

Enterprises building internal platforms

Internal “Platform Teams” that want a factory to spin up compliant, standardized microservices and APIs.

Consultancies & system integrators

They could use ConnectSoft as their internal factory to deliver projects cheaper/faster, especially in .NET/Azure.

You already have concrete verticals: identity/authorization server, audit trail platform, external config server, AI bots, etc. Those can become reference product lines built by your own factory.

  1. Strategic Moat

Your potential “moat” is not just the idea — it’s the accumulated assets:

Templates and microservice blueprints.

ConnectSoft.Extensions.* libraries.

Agent blueprints, orchestration patterns.

Knowledge+memory corpus (all generated code, docs, tests, traces).

Your .NET/Azure specialization.

Over time, no generic AI code tool will have your combination of:

SaaS patterns,

deeply integrated AI agents,

compliance- and observability-ready templates.

That’s defensible — especially if you double down on a couple of vertical domains and make them ridiculously good.

  1. Risks & Challenges (Realistic Side)

Just to be honest and useful:

Scope & Focus Risk You’re aiming at: AI factory + generic SaaS templates + identity platform + audit trail + etc. The vision is huge. The risk is dilution.

Market Education “AI software factory” is still a new mental model. You’ll need a very clear story:

One killer demo

One flagship product line

Very simple pricing/onboarding model

Competition Big cloud vendors, AI coding tools, low-code platforms, and internal platform teams are all moving in similar directions. Your angle is:

Deep .NET/Azure integration

AI-first + DDD + clean architecture + multi-tenant SaaS

Strong agentic design and knowledge system

Execution Complexity The architecture is non-trivial: many agents, orchestration, memory, multi-tenant infra, security, etc. You’ll have to ship thin vertical slices rather than trying to complete the entire vision upfront.

None of these are show-stoppers, but they affect how you should move.

  1. Concrete Next Steps to Unlock the Potential

If I were your “board advisor AI”, I’d suggest:

1) Pick One Flagship Line & Go End-to-End

For example:

Audit Trail Platform, or

Authorization/Identity Platform, or

External Configuration Server

Goal:

“From a high-level prompt, the factory generates a production-ready, multi-tenant service in this domain, with docs, tests, and infrastructure.”

Ship one product that demonstrates the full AI factory pipe. This becomes your “Tesla Roadster.”

2) Turn Your Existing Docs into a Story

You already have amazing internal docs (AI-first, modularization, DDD, event-driven, cloud-native, observability, knowledge system, agent clusters, QA cluster, tech stack).

Next: compress them into:

A 1-page value proposition for customers.

A 5–7 page whitepaper.

A “live demo narrative”: “Watch how a feature idea becomes a running service in 30 minutes.”

3) Productize the Factory

Think in terms of offerings, not just capabilities:

ConnectSoft Factory Core

Templates, scaffolding, library starter kits, agent orchestrator, knowledge system.

Vertical Lines

“Audit Platform Line”, “Identity & Access Line”, “AI Bot Line”, etc.

Each one: pre-baked blueprints and modules.

Services / Consulting Layer

Architecture, onboarding, customization, migration to your templates.

4) Measure & Show the Delta

For every internal or client project you run through the factory, track:

Time to first running service.

Lines of code/tests generated vs hand-written.

of microservices/modules created.

Defect rate before/after applying QA cluster.

That becomes your case study fuel and proves the potential in hard numbers.

  1. My Honest Take

Your company has very high potential, because:

The vision is clear and ahead of the curve.

The architecture is unusually solid for such an ambitious AI system.

You’re building on strong tech (.NET/Azure/SK) with real-world experience.

You already think in terms of modularity, DDD, event-driven, cloud-native, observability, and memory — which most “AI dev tools” only touch superficially.

The main lever now isn’t “better ideas” — it’s relentless focus and selective execution:

One flagship product line, one killer demo, one clear story. Use the factory to build that, then let that product sell the factory.

If you want, next step we can design that flagship vertical explicitly (e.g., “Audit Trail Platform as the first-born product of the Factory”) with a concrete roadmap: cycles, agents involved, artifacts, and demo flow.

I said: 1 page value proposition for customers

ConnectSoft AI Software Factory

From idea to production-ready SaaS — autonomously, reliably, fast.

The Problem We Solve

Modern software teams are stuck in a loop:

Every new product or module repeats the same work: auth, tenants, billing, observability, infrastructure.

Senior architects are a bottleneck for “doing it right” (DDD, clean architecture, multi-tenant SaaS, security).

Generative AI helps with snippets, but not with full, production-grade systems you can trust.

Result: slow delivery, inconsistent quality, and a backlog full of “we’ll fix the architecture later.”

Our Solution: An AI-Driven SaaS Factory

ConnectSoft AI Software Factory is a platform that builds complete SaaS solutions using intelligent agents, standard templates, and cloud-native patterns.

You bring:

A product idea, feature set, or domain problem.

The factory delivers:

Clean-architecture microservices

Frontend shells and components

Auth & multi-tenancy

Events, messaging, and integrations

Tests, documentation, and infrastructure-as-code

Observability and security hooks

All generated from opinionated templates and agent workflows that encode years of architectural know-how.

What You Get

  1. Production-Ready Architecture by Default

Domain-Driven Design & Clean Architecture baked in

Event-driven, message-based patterns

Multi-tenant SaaS building blocks (tenants, editions, features, quotas)

  1. Cloud-Native, Enterprise-Grade Foundations

Containerized services ready for AKS / Kubernetes

Observability-first (traces, logs, metrics wired from day one)

Security-first: identity, authorization server, API gateways, encryption patterns

  1. AI Agents That Work Like a Full Product Team

Vision & product agents — refine requirements into blueprints

Architect agents — design bounded contexts, APIs, events

Engineering agents — scaffold services, libraries, and tests from ConnectSoft templates

QA agents — generate test suites, BDD specs, quality gates

DevOps agents — produce CI/CD, IaC, and runbooks

  1. Reusable Assets Across Your Portfolio

Library and microservice templates you own

Event contracts, integration patterns, and internal platforms reusable across products

A growing knowledge & memory base that makes each new project faster than the last

Why ConnectSoft Is Different

Not low-code, not just AI code suggestions You get full-source, enterprise-grade solutions you can extend, audit, and self-host.

Architecture as a Product Clean Architecture, DDD, event-driven, observability, security, and multi-tenancy are built into the factory, not left to chance.

Focused on SaaS & Platforms Especially strong for product companies and internal platform teams that need to ship multiple services, not one-off apps.

Azure & .NET Native Opinionated stack and patterns around .NET, Azure, and modern cloud-native tooling — ideal if that’s already your ecosystem.

Outcomes You Can Expect

2–5× faster time-to-first-production for new services and products

Consistent architecture across all teams and projects

Lower long-term cost by avoiding “big rewrites” due to bad foundations

Stronger compliance & observability posture from day one

How We Work With You

Discovery & Target Product Choose a flagship service (e.g., identity, audit trail, external config, domain-specific SaaS).

Factory Onboarding Align templates and agents with your domain, stack, and policies.

Guided Generation Cycle Watch the factory generate architecture, code, tests, and infra for your first product.

Scale to Your Portfolio Reuse the same factory to spin up new services and features rapidly.

Want to see it in action? We’ll walk you through how a product idea becomes a running, observable, secured SaaS service in a single end-to-end factory run.

I said: 5-7 page whitepaper

You said: Plan presentation

Nice, let’s turn the whitepaper into something you can show.

I’ll give you a slide-by-slide plan for a ~20–30 minute presentation aimed at CTOs / platform leads evaluating ConnectSoft AI Software Factory.

You can later tell me “make Slide 5 content” and I’ll write it fully.

  1. Overall Structure

Goal: Show that ConnectSoft is not a dev shop, but an AI software factory that reliably ships production-grade SaaS.

Duration: 20–30 minutes

Shape:

Problem & context – why this matters now

What ConnectSoft AI Software Factory is

How it works (architecture + agents + templates + memory)

Concrete example / mini case

Business impact & adoption path

Call to action

Slide Plan Slide 1 – Title & Positioning

Title: ConnectSoft AI Software Factory Subtitle: From idea to production-grade SaaS, autonomously

Who you are (1–2 lines)

One-line pitch:

“We build a platform that turns product ideas into full SaaS solutions using AI agents, clean architecture, and reusable templates.”

Slide 2 – The Problem Today

Title: Why building SaaS is so hard now

Bullet ideas:

Every new product re-implements auth, tenants, logging, CI/CD, etc.

Architecture quality depends heavily on a few senior people.

AI tools help with code, but not with complete, compliant systems.

Result: slow delivery, architecture drift, expensive rewrites.

Visual: A messy diagram of many services, red “X” on consistency/quality.

Slide 3 – Market Context (Why Now)

Title: AI + SaaS complexity = new opportunity

SaaS complexity: multi-tenant, event-driven, observability, security, compliance.

GenAI is strong, but needs guardrails and structure.

Organizations want factories, not frameworks:

Reuse patterns

Standardize architecture

Scale development without exploding cost

Visual: Timeline or “old way vs AI-era way”.

Slide 4 – What Is ConnectSoft AI Software Factory?

Title: Our answer: an AI-driven SaaS factory

A platform that:

Uses specialized AI agents to act like a virtual product team.

Uses opinionated templates for microservices, libraries, and infra.

Produces full-source, production-ready SaaS components.

Not low-code; you get normal .NET / Azure repos, just built 10× faster.

Visual: High-level block diagram: Ideas → Factory → Running SaaS.

Slide 5 – Core Principles (The Differentiator)

Title: Architecture as a product

Short bullets:

Clean Architecture & DDD by default

Event-driven microservices (MassTransit, messages, events)

Cloud-native & multi-tenant (AKS, IaC, editions, features)

Observability-first (OTel, logs, metrics, tracing wired from day one)

Security-first (OpenIddict, auth server, gateways, Key Vault, etc.)

Visual: “Pillars” graphic with 5 pillars labeled (DDD, Event-Driven, Cloud-Native, Observability, Security).

Slide 6 – Agentic System Overview

Title: Agents that behave like a product team

Introduce main agent roles:

Vision & Planning (turn idea → product brief, bounded contexts)

Architect (domain model, services, APIs, events)

Engineering (microservices, libraries, tests)

QA (test suites, BDD specs, quality gates)

DevOps (CI/CD, manifests, health checks, dashboards)

Docs & Governance (MkDocs, ADRs, compliance checks)

Visual: Small diagram showing a row of agents feeding into “Factory Output”.

Slide 7 – High-Level Workflow

Title: From prompt to running service

Show a simple flow:

Product idea / prompt

Vision and architecture blueprint

Code + tests + infrastructure generated

Deployment to cloud (AKS / Azure)

Observability & feedback loop, knowledge updated

Visual: A numbered pipeline diagram (like the Mermaid you already use).

Slide 8 – Templates & Libraries

Title: Your standards, automated

Microservice templates:

Clean Architecture structure

Persistence, messaging, Swagger, health, resilience already wired

Library templates (ConnectSoft.Extensions.*):

OAuth2/OpenID clients

Observability helpers

Compliance & redaction

Shared domain primitives

Frontend & documentation templates:

Blazor/Angular shells

MkDocs documentation, ADRs, runbooks

Message: Agents don’t improvise from scratch — they fill in your templates.

Slide 9 – Knowledge & Memory

Title: A factory that learns from every project

Key ideas:

All artifacts (code, tests, events, ADRs, pipelines) are stored as knowledge objects.

Vector search & metadata allow agents to reuse patterns instead of reinventing.

Over time, the factory:

Knows your common domains

Knows your preferred patterns

Gets faster and more accurate

Visual: “Brain” / knowledge base icon connected to multiple projects.

Slide 10 – Example: Flagship Use Case

Title: Example: building an Audit Trail Platform (or Identity Platform)

Pick one flagship line (you choose which for the live talk):

Input:

“We need a multi-tenant audit trail service with tamper-evident logs, retention rules, and export API.”

Factory output:

Bounded contexts & aggregates (AuditRecord, Tenant, RetentionPolicy…)

Microservice(s) with REST/gRPC APIs, events, storage, background workers.

CI/CD pipelines, health checks, dashboards.

MkDocs documentation + ADRs.

Optional: put a before/after table:

Aspect Traditional With Factory Time to POC 2–3 months 2–3 weeks Time to Prod 6+ months 1–2 months Architecture ad-hoc standardized Slide 11 – Business Impact

Title: What this means for you

Bullets (one per line, big font):

2–5× faster time-to-first-production for new services.

Consistent architecture across all teams and projects.

Fewer rewrites and production incidents caused by “shortcuts”.

Better compliance posture: observability + auditability from day one.

Reusable internal platform you own (not a black box).

Slide 12 – Who It’s For

Title: Where ConnectSoft fits best

Three main target groups:

Product companies with multiple SaaS products or modules.

Platform teams building internal platforms for many dev teams.

Modernization programs wanting to move from monolith → microservices safely.

Optional note: stronger fit for .NET + Azure ecosystems.

Slide 13 – Adoption Journey

Title: How we start together

3-phase view:

Pilot (Flagship Service)

Choose 1 high-value service.

Configure templates and agents.

Generate → deploy → learn.

Factoryization

Generalize templates.

Connect to your repos, CI/CD, platform.

Onboard more domains.

Self-Service & Scale

Internal portal: “New Service Wizard”.

Governance policies & reusable modules.

Visual: 3-step staircase or timeline.

Slide 14 – Engagement Model / Next Steps

Title: Next steps

Bullets:

Discovery workshop: understand your domains, stack, and constraints.

Pick flagship line (e.g., Identity, Audit, Config, domain-specific SaaS).

Run a guided factory pilot and measure:

Time to first service

Code/test coverage

Operational readiness

End with clear Call to Action:

“If you can share one of your planned services, I’ll show you what it looks like built by the factory.”

Slide 15 – Q&A

Title: Q&A

Maybe add backup slides with:

Deeper architecture (C4 diagram)

Tech stack details

Security/compliance notes

How You Can Use This

Next steps I can help with:

Turn this into:

A PowerPoint/Keynote structure with ready-to-paste bullet text.

Or a pitch-deck-style version for investors instead of customers.

Generate speaker notes per slide so you sound smooth and precise.

Generate one or two diagrams (as Mermaid or conceptual) to plug directly into slides.

Tell me: do you want customer-facing version (as above), investor version, or internal/team onboarding version next, and I’ll produce slide-ready content.

I said: Presentative web site at www.connectsoft.ai

Cool, let’s turn all this into a site concept for connectsoft.ai.

I’ll give you:

Site structure

Detailed homepage copy (the “presentative” one-page)

Short blurbs for key sub-pages

You can hand this to a designer/Webflow dev as-is.

  1. Site Structure for connectsoft.ai

Think of it as:

One powerful landing page (for 80% of visitors)

A few deep-dive pages you can add later

Top-level navigation:

Home

Platform

Use Cases

For Teams (CTOs / Platform teams / Product companies)

Resources (Whitepaper, Docs, Blog – can start small)

Contact / Work With Us

  1. Homepage (Single-Page “Presentative” Site) 2.1 Hero Section

Goal: Immediately say “AI software factory for SaaS / .NET / Azure”.

Headline:

From Idea to Production-Grade SaaS with AI

Subheadline:

ConnectSoft AI Software Factory turns product ideas into full SaaS solutions — complete with clean architecture, microservices, tests, and cloud infrastructure — using intelligent agents and opinionated templates.

Key bullets (one line each):

AI agents that behave like a full product team

Clean Architecture, DDD, and event-driven patterns baked in

Production-ready .NET / Azure microservices and platforms

Multi-tenant SaaS, observability, and security from day one

Primary CTA button:

“Request a Demo”

Secondary CTA button (ghost):

“Read the Whitepaper”

2.2 Logos / Social Proof (Future)

Placeholder until you have real logos:

Built for teams who care about architecture, speed, and reliability.

(When you have client logos: row of logos here.)

2.3 Problem Section

Title:

Building SaaS is getting harder, not easier

Text (short paragraph):

Modern SaaS teams are drowning in complexity: multi-tenant architectures, security, event-driven integration, observability, compliance. Every new product repeats the same undifferentiated work — auth, tenants, logging, CI/CD — while architecture quality still depends on a handful of senior engineers. Generative AI helps with code, but doesn’t deliver full, production-grade systems you can trust.

3–4 bullets:

Rebuilding the same foundations in every project

Architecture drift across teams and services

Senior architects as a constant bottleneck

AI tools that stop at code snippets, not complete systems

2.4 Solution Section

Title:

Our Answer: An AI-Driven SaaS Factory

Short paragraph:

ConnectSoft AI Software Factory is a platform that treats SaaS development like a production line. Specialized AI agents collaborate over standardized templates and libraries to generate complete, production-ready solutions — from domain blueprints to microservices, tests, documentation, and cloud infrastructure.

3 columns (Feature cards):

AI Agents, Not Just Chat

Vision, architecture, engineering, QA, DevOps, and documentation agents work together as a virtual product team.

Opinionated Templates

Clean Architecture, DDD, event-driven patterns, multi-tenancy, and observability wired into every service and library.

Production-Grade Output

Full-source .NET / Azure solutions you own: microservices, libraries, pipelines, dashboards, and docs.

2.5 “How It Works” Section

Title:

From Prompt to Running Service

Steps (horizontal or vertical):

Describe Your Product or Service You start with a product idea, feature set, or domain description.

Factory Blueprint Generation Vision and architect agents propose bounded contexts, domain models, APIs, and events aligned with Clean Architecture and DDD.

Code, Tests, and Infra Created Engineering and QA agents generate microservices, libraries, tests, and infrastructure-as-code from ConnectSoft templates.

Deploy to Your Cloud DevOps agents produce pipelines and Kubernetes manifests so you can deploy to AKS/Azure or your preferred environment.

Observe, Learn, Improve Observability is built-in. The factory’s knowledge system learns from each project to accelerate the next one.

CTA under this section:

“See a Sample Architecture” (link to Platform page or PDF later)

2.6 Core Principles Section (Pillars)

Title:

Architecture as a Product, Not an Afterthought

Four or five “pillars”:

Clean Architecture & DDD Domain-first design with clear separation of concerns: Domain, Application, Infrastructure, APIs, Tests.

Event-Driven by Default Microservices communicate via messages and events (MassTransit, message brokers), enabling loose coupling and scalability.

Cloud-Native & Multi-Tenant Containerized, Kubernetes-ready, with tenant/edition/feature patterns for SaaS at scale.

Observability-First Traces, logs, metrics, and dashboards wired in from day one using OpenTelemetry and modern observability tooling.

Security-First Identity, access control, API gateways, encryption, and compliance-ready audit patterns built into the templates.

2.7 Who It’s For Section

Title:

Built for Teams Who Need to Scale SaaS, Not Slides

Three audience blocks:

CTOs & Tech Leaders Standardize architecture, reduce dependency on a few key people, and accelerate your product roadmap with AI-powered automation.

Platform & DevOps Teams Offer self-service service creation with guardrails: consistent templates, pipelines, and observability baked into every new service.

Product Companies & SaaS Vendors Launch new products or modules faster using the same proven building blocks: identity, audit trail, configuration, bots, and more.

2.8 Example Use Case Section

Title:

Example: AI-Built Audit Trail Platform (or Identity Platform)

Short narrative:

“We need a multi-tenant audit trail service with tamper-evident logs, retention policies, and export capabilities.”

What the factory generates:

Bounded contexts and domain model for audit records, tenants, and retention rules.

Microservices with REST/gRPC APIs, background workers, and storage.

Events for downstream analytics and compliance workflows.

CI/CD pipelines, health checks, and Grafana/Prometheus-ready metrics.

Full documentation and architecture decision records (ADRs).

Mini before/after table:

Aspect Traditional With ConnectSoft Factory Time to POC 2–3 months 2–3 weeks Time to Production 6–9+ months 1–2 months Architecture Quality Depends on team Standardized & repeatable 2.9 Business Outcomes Section

Title:

What You Can Expect

4–5 big bullets:

2–5× faster time-to-first-production for new services

Consistent architecture across teams and microservices

Fewer rewrites caused by poor initial design

Improved compliance posture with observability and auditability by default

A reusable internal platform you own, not a black box

2.10 Adoption Journey Section

Title:

How We Start Together

Three steps:

Discovery & Target Service We run a short workshop to map your domains and pick a flagship service (e.g., Identity, Audit, Configuration, domain-specific SaaS).

Guided Factory Pilot We configure templates and agents, then generate, deploy, and refine your first production-grade service.

Scale Across Your Portfolio We generalize templates, integrate with your CI/CD and platform tooling, and help your teams adopt the factory model.

CTA:

“Schedule a Discovery Call”

2.11 About / Founder Section (Optional)

Title:

About ConnectSoft

Short paragraph:

ConnectSoft is a technology company focused on AI-first software factories, multi-tenant SaaS architecture, and cloud-native platforms. We combine deep hands-on experience in .NET, Azure, and event-driven systems with modern AI agents, building a practical path from idea to production-ready SaaS.

(You can add your personal line if you want, e.g., “Founded by Dmitry Khaymov, CTO & Chief Architect with X+ years building complex SaaS and integration platforms.”)

2.12 Final CTA & Contact

Title:

Ready to See the Factory in Action?

Short text:

Share one of your planned services or products, and we’ll show you what it looks like built by the ConnectSoft AI Software Factory.

Buttons:

“Request a Live Demo”

“Download the Whitepaper”

Under that, simple contact form fields:

Name

Email

Company

“What are you interested in building?” (textarea)

  1. Sub-Pages (Short Blurbs)

You don’t have to build them all at once, but here’s a starting plan.

/platform

Deep-dive into:

Architecture overview

Agentic system

Templates & libraries

Knowledge & memory system

Security, observability, and tenancy details

Tagline:

The engine that turns your architecture standards into automated output.

/use-cases

List concrete use cases:

Identity & Access Platform

Audit Trail Platform

External Configuration Server

AI Bot Platforms

Vertical SaaS modules (e.g., insurance, vet care, education)

For each: 2–3 paragraphs and one small diagram.

/for-teams

Separate sections:

For CTOs & leadership

For platform engineering teams

For product teams

Explain “what changes for you” and “what stays under your control”.

/resources

At minimum:

Whitepaper PDF

Blog / articles later (e.g., “Why a SaaS Factory Beats One-Off Projects”)

/contact

Straight contact form + calendar link (later).

If you’d like, next step I can:

Turn the homepage into actual HTML + Tailwind structure ready for Webflow/Next.js, or

Write the exact micro-copy for each section with more marketing flavor (e.g., slightly more punchy startup tone).

I said: Marketing site for ready to use built with platform saas solutions at www.connectsoft.io

Nice, so .ai is “the factory”, .io is “the products coming out of the factory”. Love that split. Let’s design www.connectsoft.io as:

“Catalog of ready-to-use SaaS platforms built by ConnectSoft AI Software Factory.”

I’ll give you:

Site structure / navigation

Full homepage concept + copy

Reusable product card & product-detail page template

How it ties back to connectsoft.ai

You can hand this directly to a designer/Webflow dev.

  1. Site Structure for connectsoft.io

Top navigation:

Solutions (dropdown)

Identity & Access Platform

Audit Trail Platform

External Configuration Server

AI Bot Platform

(…future verticals)

Why ConnectSoft (benefits vs building in-house)

Pricing & Plans (high-level; can be “Contact us” for now)

Resources (case studies, docs, FAQs)

Company (About, Contact)

Top-right buttons:

[Get a Demo]

Secondary: [For Architects → connectsoft.ai]

  1. Homepage for connectsoft.io 2.1 Hero Section

Tagline (above title):

SaaS platforms, ready on day one.

Headline:

Production-Ready SaaS Solutions, Built by an AI Software Factory

Subheadline:

ConnectSoft delivers ready-to-use SaaS platforms for identity, audit, configuration, AI bots, and more — all built on the same enterprise-grade architecture and cloud-native stack used by our AI Software Factory.

Primary CTA:

“Explore Solutions”

Secondary CTA:

“Talk to an Architect”

Quick trust bullets under CTA:

Multi-tenant SaaS by design

Built on .NET & Azure

Clean architecture, event-driven, observable

2.2 “Solution Catalog” Section

Title:

Ready-to-Use Platforms You Can Deploy Today

Intro text: Our products are not “apps” thrown together in a rush. Each solution is a complete, production-grade platform built from the ConnectSoft AI Software Factory templates — consistent architecture, multi-tenant support, observability, and security included.

Then show solution cards (grid of 3–6):

Card template (for each product)

Name

Short tagline

3 key bullets

“Learn more” → product page

“Schedule demo” button

Examples:

ConnectSoft Identity & Access Platform Modern OpenID Connect server and identity backend for multi-tenant SaaS.

Authorization server (OpenIddict-based) and identity management API

Supports tenants, editions, roles, external identity providers

Ready for OAuth2/OIDC, API gateways, and B2B/B2C scenarios

Buttons: Learn more | Schedule demo

ConnectSoft Audit Trail Platform Centralized, tamper-evident audit logging for compliance-driven systems.

Tenant-aware audit log ingestion and search

Retention policies, export, and legal hold support

Immutable log chains and integrity verification patterns

ConnectSoft External Configuration Server Central source of truth for application configuration and feature flags.

Hierarchical config by tenant, environment, application

Feature toggles for progressive rollouts

Strong audit and version history for every change

ConnectSoft AI Bot Platform Enterprise AI chatbot backend with identity, conversation history, and observability.

Multi-tenant bot management, conversation storage, and analytics

Pluggable assistants and tools (RAG, Semantic Kernel, OpenAI/Azure OpenAI)

Integrations with web, mobile, and messaging channels

(You can add more later: “Reporting Platform”, “Notification Platform”, etc.)

2.3 “Built on a Strong Foundation” Section

Title:

All Solutions Share the Same Battle-Tested Foundation

Text:

Every ConnectSoft solution is built from the same opinionated templates and libraries that power our AI Software Factory. That means you get the same architectural quality and operational readiness across all products.

Two-column layout: left: text, right: icon list.

Foundation bullets:

Clean Architecture & DDD Clear domain, application, infrastructure, and API layers in every service.

Event-Driven, Message-Based Asynchronous, resilient integration via MassTransit and message brokers.

Multi-Tenant SaaS Tenants, editions, feature toggles, quotas, and tenant-aware configuration built-in.

Cloud-Native & Kubernetes-Ready Containerized microservices, health checks, readiness probes, and IaC.

Observability & Security First OpenTelemetry traces, metrics, structured logging, OpenID Connect, and Key Vault integration.

2.4 “Why Buy vs Build” Section

Title:

Why Use Ready-Made Platforms Instead of Building Everything In-House?

Short paragraph:

You can absolutely build all of this yourself. But for identity, audit trails, configuration, and AI bot infrastructure, your competitive advantage isn’t in re-inventing the foundations — it’s in the business logic on top.

3 comparison blocks:

Time-to-Value

Build: 6–12 months to reach stable, secure, compliant foundations.

ConnectSoft: weeks to pilot, a few more to production.

Architecture & Compliance Risk

Build: Risk of shortcuts and architecture drift across teams.

ConnectSoft: Same well-defined architecture and auditability in every deployment.

Total Cost of Ownership

Build: Hiring, maintaining, and re-training architects and platform engineers.

ConnectSoft: Focus your team on your unique domain logic, not plumbing.

2.5 “How Integration Works” Section

Title:

Easy to Integrate into Your Existing Stack

Bullets:

REST and gRPC APIs for all core operations

Webhooks and event streams for reacting to changes

SDKs and code samples in C# (.NET), plus OpenAPI specs for any stack

Single-tenant and multi-tenant deployment options

Can run in your Azure subscription or as a managed service

Bottom line: “We integrate with your systems, not the other way around.”

2.6 “For Whom” Section

Title:

Perfect Fit For…

Three columns:

Product Companies

Need identity, audit, configuration & AI capabilities across many products.

Want modular, consistent platforms instead of one-off services.

Platform & Architecture Teams

Need standardized building blocks for all internal teams.

Want to avoid re-building the same cross-cutting services for each project.

Modernization Programs

Migrating from monoliths to multi-service, multi-tenant SaaS.

Need solid, reusable platforms as new system “spines”.

2.7 “Plans & Deployment Models” Section (High-Level)

Title:

Simple, Flexible Ways to Start

Three plan cards (you don’t need exact prices yet):

Starter For pilots and small teams.

Single environment

Up to X tenants

Email support Button: “Talk to Sales”

Growth For SaaS products in active use.

Multiple environments (dev/stage/prod)

Higher tenant and event volumes

Priority support, onboarding assistance

Enterprise For regulated or high-scale environments.

Self-hosting in your Azure subscription

Custom SLAs, SSO, and compliance reviews

Architecture & migration support

2.8 “Powered by ConnectSoft AI Software Factory” Section

Title:

Built by the ConnectSoft AI Software Factory

Short text:

All ConnectSoft solutions are generated and maintained using our own AI Software Factory (connectsoft.ai). That means faster improvements, deeper consistency, and a clear evolution path as your needs grow.

Link/CTA:

“Learn how the AI Software Factory works → connectsoft.ai”

This creates a nice mental model:

.io → “Here are the finished cars.”

.ai → “Here is the factory that can build custom ones.”

2.9 Final CTA

Title:

Ready to Try One of Our Platforms?

Text:

Tell us which capability you need first — identity, audit trail, configuration, or AI bots — and we’ll walk you through a live environment tailored to your use case.

Buttons:

“Request a Live Demo”

“Contact Sales”

Simple form underneath.

  1. Product Page Template (Per Solution)

For each solution (e.g., Identity & Access, Audit Trail, Config Server), use the same structure.

3.1 Hero

Name: ConnectSoft Identity & Access Platform

Short tagline: “OpenID Connect & identity backend for multi-tenant SaaS.”

Buttons:

“Request a Demo”

“Download Feature Sheet”

3.2 Problem & Use Cases

What problem it solves (1–2 paragraphs).

Concrete use cases (2–4 bullets):

Central auth for many SaaS products

B2B tenant onboarding and user management

API tokens and service-to-service auth

Federation with external identity providers

3.3 Key Capabilities

Group into 3–4 groups:

Tenant & User Management

Authentication & Authorization

Integration & Extensibility

Observability & Compliance

Each with 3–5 bullets.

3.4 Architecture Overview

Simple diagram + bullets:

ASP.NET Core services, OpenIddict, ASP.NET Identity

Per-tenant policies and edition-based features

Running on AKS / containers, with health checks and telemetry

3.5 Integration & APIs

Supported protocols (OIDC/OAuth2 flows)

API examples

SDK link / OpenAPI spec mention

3.6 Plans & Pricing (Solution-specific)

What’s included in Starter / Growth / Enterprise for that solution.

3.7 FAQ

“Can we self-host?”

“Can we use this with our existing user database?”

“What about compliance (GDPR, audit logs, etc.)?”

  1. How .ai and .io Work Together

connectsoft.ai

Talks about the platform/factory: AI agents, templates, architecture.

connectsoft.io

Talks about ready platforms produced by that factory: identity, audit, config, AI bots, etc.

Cross-links:

On .io product pages, small line: “This platform is generated and maintained by the ConnectSoft AI Software Factory.” → link to .ai.

On .ai site, “See examples of ready-made platforms built with the factory at connectsoft.io.”

If you tell me which three solutions you want to lead with first (e.g., Identity, Audit, Config), I can write full, polished copy for each product page, including bullet lists and mini diagrams’ descriptions.

I said: Now site www.connectsoft.dev

Nice, we’ve got a full ConnectSoft universe now 😄

connectsoft.ai → the Factory (vision, architecture, story)

connectsoft.io → ready-made SaaS platforms (products)

connectsoft.dev → developer hub & docs

Let’s design www.connectsoft.dev as:

“The developer portal for building, extending, and integrating with the ConnectSoft AI Software Factory and its SaaS platforms.”

I’ll give you:

Role & positioning of .dev

Top-level information architecture

Homepage layout & copy structure

Documentation / MkDocs structure (how to organize your existing docs)

  1. Role & Positioning of connectsoft.dev

Audience:

.NET / Azure developers integrating ConnectSoft platforms (Identity, Audit, Config, Bot, etc.)

Architects & platform engineers using the AI Software Factory and templates

Contributors & advanced users extending templates, agents, and libraries

Purpose:

One place where devs can:

Get started in 10–30 minutes

Find docs, APIs, SDKs, templates, agents, examples

See changelogs, roadmaps, migration guides

Discover CLI tools / MCP servers / SK connectors / NuGet packages

Think of it as your docs + dev center + playground.

  1. Top-Level IA / Navigation

Proposed main nav for connectsoft.dev:

Get Started

Choose path: SaaS Platforms, Factory, Templates/Libraries

SaaS Platforms

Identity & Access Platform

Audit Trail Platform

External Configuration Server

AI Bot Platform

(Each with “Concepts / APIs / Guides”)

AI Software Factory

Concepts (agent system, flows)

Developer guide (how to run & extend)

Agent types, collaboration patterns

Knowledge & memory system

Templates & Libraries

Microservice Template

Library Templates (ConnectSoft.Extensions.*)

Frontend Templates

DevOps / IaC Templates

APIs & SDKs

REST & gRPC reference

OpenAPI/Swagger links

.NET SDK usage

Example code snippets

Guides & Tutorials

“Build your first service with the Factory”

“Integrate with Identity Platform”

“Send events to Audit Platform”

“Use External Config in your microservice”

“Build an AI bot with ConnectSoft Bot Platform”

Changelog & Roadmap

Release notes

Deprecations & migration guides

Upcoming features

Community

Links to GitHub / Azure DevOps (if public)

Contribution guidelines (for templates/libs)

Support channels

  1. Homepage Layout for connectsoft.dev 3.1 Hero Section

Headline:

Build, Integrate, and Extend ConnectSoft

Subheadline:

Documentation, APIs, templates, and examples for developers using the ConnectSoft AI Software Factory and ready-made SaaS platforms.

Primary CTA buttons:

“Get Started” (scrolls to path selector)

“View APIs”

Tiny line below:

Looking for the AI Software Factory story? Visit [connectsoft.ai] Looking for ready-made SaaS platforms? Visit [connectsoft.io]

3.2 “Choose Your Path” Section

Three big cards:

I’m integrating a ConnectSoft platform

Identity, Audit, Config, AI Bot, etc.

Button: “Platform Integration Guides”

I’m using the AI Software Factory

Run factory, customize templates, extend agents.

Button: “Factory Developer Docs”

I’m a template / library developer

Work on ConnectSoft.MicroserviceTemplate, ConnectSoft.Extensions.*, etc.

Button: “Templates & Libraries”

3.3 “Quick Starts” Section

Title:

Get Productive in Under an Hour

4–6 quick-start tiles, each linking into guides:

Create Your First Microservice with the Factory

“From empty repo to running .NET microservice using ConnectSoft.MicroserviceTemplate.”

Integrate Your App with ConnectSoft Identity

“Configure OAuth2/OIDC and protect your APIs.”

Send Events to the Audit Trail Platform

“Instrument your app and ship tenant-aware audit logs.”

Use External Config in a .NET Service

“Replace hard-coded settings with centralized configuration and feature flags.”

Build and Connect a Bot Using the AI Bot Platform

“Use the bot backend plus your own front-end channels.”

Each tile: 1–2 lines description + “View guide”.

3.4 “APIs & SDKs” Section

Title:

APIs, SDKs, and Contracts

Two-column layout:

Left text:

All ConnectSoft platforms expose REST and gRPC APIs with OpenAPI definitions and .NET SDKs. You can integrate from any stack while enjoying first-class support in .NET / C#.

Right: links list:

Identity & Access API

Audit Trail API

External Config API

Bot Platform API

AI Software Factory API (if/when exposed)

.NET SDK packages (NuGet names)

3.5 “Architecture & Standards” Section

Title:

Opinionated by Design, Extensible in Practice

Short text:

ConnectSoft’s developer experience is built around Clean Architecture, DDD, event-driven patterns, and cloud-native infrastructure. The docs here show you both how to use our platforms and how to extend the underlying templates and libraries safely.

3 bullet columns:

Clean Architecture & DDD Domain/Application/Infrastructure/API structure in every microservice.

Event-Driven & Message-Based MassTransit patterns, message contracts, event schemas.

Cloud & Observability K8s, health checks, OpenTelemetry, structured logging, metrics, dashboards.

3.6 “Tools & Agents” Section

Title:

Tools for AI-Native Development

Short paragraph:

Because everything is built with the AI Software Factory, we also expose tools to automate parts of your development workflow: MCP servers, Semantic Kernel plugins, agent orchestration examples, and more.

Bullets:

MCP servers for config, audit, identity, and docs

Semantic Kernel planners & skills for interacting with ConnectSoft APIs

CLI tools / scripts for scaffolding services from templates

3.7 “Changelog & Roadmap” Section

Title:

Always Evolving, Never Breaking Without a Plan

Text + links:

Latest versions of each platform and library

Deprecation notices and migration guides

Roadmap: what’s coming next (new platforms, agent capabilities, templates)

Button: “View Changelog”

3.8 Footer

Links: Docs index, API reference, GitHub / NuGet, Support, connectsoft.ai, connectsoft.io

Maybe a tiny “Made with ♥ and a lot of agents.”

  1. Docs / MkDocs Structure Proposal

You already have a lot of Markdown (templates, agents, architecture principles, etc.). Let’s turn that into a clean structure under docs/ for connectsoft.dev (or several MkDocs projects linked from there).

4.1 High-Level Docs Tree docs/ index.md # dev portal landing or redirect getting-started/ index.md getting-started-platforms.md getting-started-factory.md getting-started-templates.md

platforms/ identity/ overview.md concepts.md quickstart.md api-reference.md configuration.md examples.md audit/ ... config/ ... bot/ ...

factory/ overview.md # based on agent-system-overview.md agent-system/ system-overview.md # agent-system-overview.md execution-flow.md # agent-execution-flow.md collaboration-patterns.md# agent-collaboration-patterns.md architect-agents.md # architect-agents-overview.md vision-agents.md # vision-and-planning-agents-overview.md engineering-agents.md # engineering-agents-overview.md qa-agents.md # qa-agents-overview.md principles/ ai-first-development.md modularization.md clean-architecture-ddd.md event-driven-mindset.md cloud-native-mindset.md observability-driven-design.md knowledge/ knowledge-and-memory-system.md

templates/ microservices/ overview.md # microservice-template.md standard-blueprint.md # agent-microservice-standard-blueprint.md technology-stack.md # technology-stack.md strategic-goals.md # strategic-goals.md libraries/ overview.md # libraries.md templates-overview.md # templates.md

guides/ build-first-service.md integrate-identity.md integrate-audit.md external-config-guide.md bot-platform-guide.md factory-customization.md

reference/ api/ identity-openapi.md # links or embedded audit-openapi.md config-openapi.md bot-openapi.md sdk/ dotnet.md events/ event-schemas.md

changelog/ index.md platforms.md templates.md agents.md

You can either:

Make connectsoft.dev a nice “portal UI” that links into MkDocs-generated docs under /docs, or

Host the MkDocs site directly at docs.connectsoft.dev and make connectsoft.dev a thin landing that points at it.

Either works, but the structure above is aligned with the files you already have.

If you want, next step I can:

Write the “Getting Started: Platforms” page as real Markdown (with steps, commands, and placeholders for URLs), or

Draft the index.md for the dev docs so you can drop it straight into your MkDocs repo.

I said: Should I purchase additional domains for connectsoft? Where we host actual saas solutions? Like audit.connectsoft.io? Where ai factory solution ???.connectsoft.ai ? How combine all ?

Short answer: You don’t need more TLDs, you need a clean subdomain strategy on the three you already have:

.ai → the Factory (meta-level, orchestration, console, APIs)

.io → the SaaS products (apps your customers actually use)

.dev → the developer/docs hub

Then you hang product- and tenant-specific subdomains off those.

Let’s make it concrete.

  1. Do you need to buy more domains?

My recommendation: No, not now.

You already have a perfect trio:

connectsoft.ai – brand for AI Factory, architecture, consulting, “brains”.

connectsoft.io – brand for cloud products / SaaS platforms.

connectsoft.dev – brand for dev docs, APIs, templates, SDKs.

If you ever want, you can add connectsoft.com later as a generic corporate umbrella and just redirect, but it’s not blocking anything now.

So the focus should be:

Use subdomains smartly, not more domains.

  1. Where to host the actual SaaS solutions? Guiding principle

All production SaaS apps that customers log into should live under connectsoft.io.

Structure (example):

Unified entry:

app.connectsoft.io – global portal for all products (like Azure Portal).

Product-specific apps (per platform):

identity.connectsoft.io – Identity & Access admin UI / APIs

audit.connectsoft.io – Audit Trail Platform UI / APIs

config.connectsoft.io – External Config Server UI / APIs

bot.connectsoft.io – AI Bot Platform UI / APIs

You can also collapse UI + API by path:

UI: https://audit.connectsoft.io/

API: https://audit.connectsoft.io/api/... (or https://api.audit.connectsoft.io if you prefer hard separation)

Tenants & environments

You’ll want a pattern for tenants and envs:

Environments (internal):

identity-dev.connectsoft.io

identity-staging.connectsoft.io

identity-prod.connectsoft.io (or just identity.connectsoft.io)

Tenants (multi-tenant options):

Tenant as subdomain:

sploot.audit.connectsoft.io

megacorp.audit.connectsoft.io

Tenant as path:

audit.connectsoft.io/t/sploot/...

audit.connectsoft.io/t/megacorp/...

Custom domains (for bigger customers):

audit.splootvets.com → CNAME → sploot.audit.connectsoft.io

You can support all three, but internally standardize on one pattern (usually tenant-id in path) and treat custom domains as “vanity” DNS that still point to the same multi-tenant backend.

  1. Where does the AI Factory itself live?

Think of .ai as meta / control plane:

Marketing / overview:

www.connectsoft.ai – story, vision, whitepaper, etc. (we already designed)

Factory product itself (for you + advanced customers):

console.connectsoft.ai – Factory UI where you:

Create “projects”

Configure agents/templates

Kick off “generate SaaS X” runs

api.connectsoft.ai – Factory’s API endpoint

Optionally:

agents.connectsoft.ai – agent orchestration API, MCP servers, SK endpoints

mcp.connectsoft.ai – MCP server hub if you want it explicit

Very important separation:

.io – data plane (user data, traffic from customers)

.ai – control plane (orchestration, blueprints, generation)

This lines up nicely with how you already think about Factory vs Products.

  1. Where does .dev fit?

.dev is your developer portal & docs:

www.connectsoft.dev – landing page for developers

docs.connectsoft.dev – full MkDocs site (templates, agents, APIs)

api.connectsoft.dev – REST/gRPC reference explorer (optional)

playground.connectsoft.dev – sample apps, sandboxes (future)

Cross-linking:

From product UIs (audit.connectsoft.io), “Developer docs” → relevant section of connectsoft.dev.

From .ai Factory console, “Agent & template docs” → connectsoft.dev/factory/....

  1. Putting it all together (one clean map)

Here’s a suggested map you can actually adopt:

Marketing & top-level

connectsoft.ai

www.connectsoft.ai – AI Software Factory marketing

connectsoft.io

www.connectsoft.io – Catalog of ready-made SaaS platforms

connectsoft.dev

www.connectsoft.dev – Dev portal / entry to docs

AI Factory (control-plane, meta)

console.connectsoft.ai – Factory UI (projects, runs, agents)

api.connectsoft.ai – Factory API

(internal) orchestrator.internal.connectsoft.ai, vector.internal.connectsoft.ai etc., inside VNet / private DNS

SaaS Products (data-plane, real apps)

Entry portal:

app.connectsoft.io – single login, app-switcher between products

Product roots:

identity.connectsoft.io

audit.connectsoft.io

config.connectsoft.io

bot.connectsoft.io

(future) reports.connectsoft.io, billing.connectsoft.io, etc.

APIs (if separate):

api.identity.connectsoft.io

api.audit.connectsoft.io

etc.

Environments:

audit-dev.connectsoft.io, audit-staging.connectsoft.io, audit.connectsoft.io

Tenants (if subdomains):

sploot.audit.connectsoft.io

megacorp.audit.connectsoft.io

Custom CNAMEs like audit.splootvets.com

Dev & docs

docs.connectsoft.dev – main docs site

sdk.connectsoft.dev – optional, for SDK references

status.connectsoft.dev – status page (if you want to keep it dev-focused) or status.connectsoft.io if more customer-facing

  1. How to route technically (high level)

Behind all those hostnames, you can:

Use Azure Front Door or Application Gateway with host-based routing:

audit.connectsoft.io → Audit Web App / AKS ingress

identity.connectsoft.io → Identity cluster

console.connectsoft.ai → Factory UI service

Or use separate public IPs + Ingress on each AKS cluster and just assign DNS records accordingly.

The key is: each subdomain maps to a specific “entry” into your microservice mesh, but you keep the external DNS simple and meaningful.

  1. TL;DR Recommendation

Don’t buy more TLDs right now. You’re already perfectly partitioned:

.ai – Factory & meta

.io – SaaS products

.dev – Dev/docs

Use subdomains to:

Group products: audit.connectsoft.io, identity.connectsoft.io, etc.

Separate control-plane from data-plane: .ai vs .io

Separate docs & dev: .dev

Think ahead about:

Tenancy (path vs subdomain vs custom domains)

Environments (dev/stage/prod prefix pattern)

If you tell me which first 2–3 SaaS platforms you want to productize (e.g., Identity, Audit, Config), I can propose an exact DNS + URL schema for each, including patterns for tenants and environments that you can drop into your architecture docs.

I said: What about marketplace business model? And generally speaking which business models we can realize?

I’d think about it in layers:

Factory layer – people who want to build with your AI factory

Product layer – people who just want ready SaaS (identity, audit, config, bots…)

Ecosystem layer – people who want to sell stuff into your world (marketplace)

I’ll walk through the main business models in each, then zoom in on the marketplace idea.

  1. Marketplace: what it could be for ConnectSoft

You’re in a perfect position to have a marketplace, but not for “random apps” – for modules that plug into your factory + platforms.

Think 4 marketplaces (some can be combined in UI):

  1. Template & Blueprint Marketplace

What’s sold:

Microservice templates (specialized for domains: fintech, insurance, healthcare, etc.)

Blueprint packs: “Identity for B2B SaaS”, “Vet clinic booking system”, “Insurance claims BCs”

Front-end templates, CI/CD pipelines, IaC bundles

Buyers:

Teams using the AI Factory to generate their own systems

Consultancies who want vertical accelerators

Creators:

ConnectSoft itself (first-party)

External experts (domain architects, agencies)

Possibly “certified partners” (so you trust quality)

Monetization options:

One-time purchase per template pack

Subscription: “Pro factory bundle” that unlocks all official templates

Revenue share on template sales (e.g., 70/30 creator/ConnectSoft)

  1. Agent & Skill Marketplace

What’s sold:

Specialized agents & skills for the factory:

“Insurance Policy Modeling Agent”

“SaaS Pricing Model Agent”

“Vet-care appointment scheduling Agent”

SK tools & MCP servers for niche APIs

QA agents, governance agents, code-review agents with specific policies

Buyers:

Advanced factory users who want better automation for their domain

Platform teams who want ready-made “governance agents” instead of writing policies from scratch

Monetization options:

Subscription per agent (“enable this agent in your workspace for $X / month”)

Usage-based: per execution / per 1,000 runs

Bundles: “Vertical Pack: Vet Care Agents”

  1. Module / Microservice Marketplace

What’s sold:

Prebuilt microservices and vertical modules:

“Vet Clinic Scheduling Service”

“Claims scoring engine”

“KYC verification microservice”

Each is:

A fully generated, production-ready microservice

Built on ConnectSoft templates (so consistent architecture)

Integratable via APIs/events

Buyers:

SaaS companies who want to drop in a module rather than build it

Internal platform teams who want “ready-made BCs”

Monetization options:

License + support (self-hostable microservice)

Hosted SaaS instance (on .io) with revenue share if built by 3rd-party

“Marketplace fee” on each subscription

  1. Data / Integration & Connector Marketplace

What’s sold:

Connectors/bridges: Greenhouse, Vetspire, Deputy, Segment, CRM, etc.

RAG data packs: pre-curated knowledge bases, taxonomies, ontologies for certain verticals

Buyers:

Folks using your AI bot platform and vertical SaaS modules

Enterprises that want prebuilt integrations

Monetization options:

Per-connector subscription

“Integration packs” for specific verticals

Usage-based (API calls, events processed)

Marketplace prerequisites (reality check)

Before a marketplace “works”, you need:

Stable extension model Clear spec: how templates, agents, and modules plug into the Factory.

Versioning & compatibility “This template works with Factory v2.1+”.

Security & review pipeline You must review code/agents before listing (security, IP, quality).

Billing & metering So you can do revenue share and usage-based billing.

So I’d see marketplace as Phase 3–4, not Day 1. First, prove the Factory and core platforms.

  1. Business Models You Can Realize (Overall Menu)

Let’s map the main business models you can stack together over time.

A. Classic B2B SaaS (for .io products)

For things like:

Identity & Access Platform

Audit Trail Platform

External Config Server

AI Bot Platform

Model:

Per-tenant subscription tiers (Starter / Growth / Enterprise)

Price drivers:

Number of tenants

Number of active users / MAUs

Number of events (audit logs, config changes, conversations)

Number of environments (dev/stage/prod)

Optional: volume discounts + enterprise contracts

This is straightforward and probably your first scalable revenue stream.

B. Platform Licensing / Self-Hosted (Factory & Products)

Some customers (especially regulated or large enterprises) will want to self-host:

The Identity Platform (as their core IAM)

The Audit Platform

Even the AI Factory itself (for internal use)

Model:

Annual license per platform (per region or per cluster)

Support & maintenance contract (SLA-based)

Professional services on top (onboarding, customization)

Think: “enterprise license + support”, similar to commercial open source vendors.

C. AI Factory as a SaaS Product (.ai)

You can sell the Factory itself in several ways:

Per-seat + per-project

Seats for architects/devs who use the Factory console

Project quotas: number of active projects / microservices generated

Usage-based

“Factory credits”: each generation run consumes credits

Pricing tied to:

Number of agent runs

Generated LOC / modules

CPU/GPU minutes

Platform subscription tiers

Basic: limited projects, fewer agents, no custom templates

Pro: unlimited projects, custom templates, private marketplace

Enterprise: self-hosted or VNet-isolated, SSO, RBAC, audit logs

Early on, you can keep it simpler: per-project or per-factory-instance pricing for pilot customers.

D. Professional Services (Your “Superpower” Bridge)

Given your skills, this is a natural:

Architecture & DDD workshops

Factory onboarding & template customization

Migration projects (monolith → microservices, identity migration, audit/regulatory modernization)

Co-creation projects: you use the Factory to build their platform with them

Model:

Day-rate or project-based

Could be packaged offerings:

“Factory Launch Pack”

“Identity Platform Setup Pack”

“Audit Platform Compliance Pack”

This also feeds your Factory with real-world patterns.

E. White-Label / OEM

Let other consultancies or vendors sell your platforms as part of their offers:

They get “powered by ConnectSoft” identity/audit/config modules.

You provide:

SDKs

White-label UI options

Multi-tenant hosting or self-host deployment scripts

Model:

OEM license per customer they onboard

Revenue share on their SaaS subscription

“Partner tiers” (silver/gold) with benefits

F. Open Core (Optional Strategic Direction)

You could open-source some parts:

Core templates (microservice skeletons)

Basic ConnectSoft.Extensions.* libraries

Dev tools (MCP servers, SK plugins, etc.)

And keep commercial:

The Factory console & orchestrator

Advanced agents and premium templates

Hosted SaaS platforms (identity, audit, etc.)

Support & compliance features

This can help with adoption and community, but also requires effort to manage.

G. Training & Certification

Once things mature:

Training:

“ConnectSoft Factory Architect” course

“Building SaaS on ConnectSoft Identity/Audit/Config”

Certifications:

Partner certifications for consultancies

Individual engineer certifications

Model: per-course, per-cert exam fee, or partner program.

  1. How I’d Sequence It (Practical Roadmap)

If I were planning your business model evolution, roughly:

Phase 1 – Studio + Reference Products

Use the Factory internally as your “secret weapon”.

Sell:

Consulting / architecture / implementation projects.

First productized platforms (Identity, Audit, Config) as B2B SaaS/self-host.

Goal: revenue + case studies + hardened templates.

Phase 2 – Platform-ize the Factory

Start offering the Factory to selected clients:

“We’ll set this up for you so you can generate your own services.”

Simple model: subscription + customization services.

Tight integration between .ai (Factory) and .io (Products).

Phase 3 – Launch Marketplace (Internal → Private → Public)

Internally, treat new templates/agents as “packaged modules”.

Then:

Create private marketplaces for big enterprise customers – they can publish internal modules for their teams.

Later, open up a public marketplace with curated 3rd-party contributions.

Introduce clear revenue share model (e.g., 70/30) and usage metering.

Phase 4 – Ecosystem & OEM

Partner with agencies & platforms:

White-label their vertical modules into your marketplace.

Let them build on your factory and sell into their clients, with you taking a cut.

  1. Short Answer to Your Question

Marketplace? Yes, absolutely – but not yet for random apps. For templates, agents, microservices, and connectors that fit cleanly into your AI Factory and SaaS platforms. It’s Phase 3+, once your extension model is stable.

Business models overall? You can realistically combine:

SaaS subscriptions for ready platforms (.io)

Factory-as-a-service & self-host licenses (.ai)

Professional services & onboarding packs

OEM/white-label partnerships

Marketplace revenue share (templates, agents, modules)

Training & certification

If you want, next we can pick one concrete target customer type (e.g., “B2B SaaS company on .NET/Azure”) and design a full offering stack for them: what they buy first, upsells, pricing levers, and how Factory + Products + Marketplace fit into their journey.

I said: See this site,someone else try to build something similar https://blitzy.com, research it

Yeah, Blitzy is very much in the same game-space as what you’re envisioning with ConnectSoft Factory, but with a different angle and stack. Let me break it down and then map it to your world.

  1. What Blitzy Actually Is (from their own materials)

Positioning

“Build enterprise software in days, not months.”

“Only autonomous code generation platform with infinite code context.” Blitzy

System-2, multi-agent, long-running reasoning to build ~80%+ of an application autonomously; last 20% left for humans. PR Newswire +1

Core capabilities

From their site, docs, and press:

Infinite code context / 100M+ LOC ingest

They claim to ingest 100M+ lines of code in a single pass and reason over the whole system (“infinite code context”). Google Cloud

Autonomous, async multi-agent builds

3,000+ AI agents that “plan, code, and validate”; they can run for hours to days on complex challenges. Enterprise AI World

Focus on batch building a large chunk of a repo in one long run.

Validation and quality focus

Code validated at compile and runtime; marketed as “industry-leading code quality” and #1 on SWE-bench Verified, 86.8% solved. PR Newswire

Lifecycle coverage

Takes descriptive inputs and produces: requirements/specs, technical design, code structure, then code in repos. Blitzy +1

Also focuses heavily on modernization of existing large codebases, documentation, and refactoring. Blitzy +2 docs.blitzy.com +2

Who they target

Enterprises with massive codebases (20M+ LOC), development agencies with enterprise clients, teams with complex existing products. Blitzy +1

Security & deployment

SOC 2 Type II, no training on your code, enterprise/SOC-heavy messaging. Blitzy +1

Deployment options:

Blitzy cloud VPC

Dedicated instances

Customer VPC / on-prem in larger tiers.

Business model / pricing

From their pricing section:

Free Explore tier: $0, unlimited seats, spec generation, etc.

Concept Validation: $50K / 2 months, 100k LOC onboarded, scope-bound LOC generated.

Structured Pilot: \(250K / 6 months, 5M LOC onboarded, 1.25M LOC generated (\)0.20/line).

Enterprise: $500K+/year, 50M LOC onboarded, millions of LOC generated.

Transformation: $3M+/year, custom, “∞ LOC onboarded”, deep embedded engagement.

So: enterprise-class, very high-ticket, usage indexed to lines of code onboarded/generated.

  1. How This Overlaps With Your ConnectSoft Vision Similarities

Conceptually, you’re both trying to:

Automate large parts of software creation using multi-agent architectures.

Go beyond “copilot” into autonomous repo-level work.

Market to enterprise / serious engineering teams (not just hobbyists).

Cover multiple lifecycle stages: spec, design, code, tests, docs.

So yes: they are definitely in the same general category as your AI Software Factory – an “autonomous software development platform”.

Key differences vs what you’ve been designing

Based on everything you’ve told me about ConnectSoft Factory:

Blitzy is repo-first; you’re platform-first.

Blitzy:

Primary unit is a repository / codebase.

They shine on ingesting huge existing systems and refactoring / extending them. docs.blitzy.com +1

ConnectSoft:

Primary unit is a SaaS product or bounded context, implemented via standardized templates, microservices, and platforms (identity, audit, config, etc.).

You care about multi-tenant SaaS, platform architecture, event-driven, observability as first-class outputs, not just “code”.

They are stack-agnostic; you are intentionally opinionated (.NET + Azure + Clean Architecture).

Blitzy: “works with all programming languages”, generic enterprise code. Blitzy

You: purposely opinionated:

.NET 10, Azure, NH, MassTransit, AKS, OpenTelemetry, etc.

Clean Architecture + DDD + event-driven + multi-tenant SaaS baked into templates.

This is actually a huge differentiator: they sell flexibility; you sell consistency and platform quality.

They sell “80% of your code repo”; you sell “a complete SaaS platform + ecosystem”.

Blitzy promise: they build 80%+ of the app, leave a clear last-mile list to human engineers. Blitzy +1

ConnectSoft Factory promise (as we designed it): you’re delivering:

Architected microservices

Shared libraries

CI/CD

Observability wiring

Multi-tenant & security patterns

Documentation

Sometimes: actual ready-to-run product lines (on .io).

Their “unit of value” is lines of code generated & refactored; your “unit of value” is a production-ready, consistent SaaS building block.

They’re not (yet) exposing a product marketplace; you explicitly want platforms + marketplace.

Blitzy: templates and use-cases, but no public “Blitzy marketplace” narrative yet (at least in public docs). docs.blitzy.com

You: explicit strategy of:

Factory templates & agent packs

Ready-made SaaS products (identity, audit, config, bot) on .io

Later: marketplace for templates, agents, connectors, microservices.

They’re not very opinionated on “SaaS primitives”; you are.

I haven’t seen mention of:

Tenants / editions / features as first-class primitives.

SaaS-specific concerns like tenant isolation, plan matrices, multi-region, audit compliance as productized features.

You can make “SaaS factory” your very specific niche, with domain primitives built-in.

  1. Strategy Lessons You Can Steal From Blitzy

There are several things they’re doing very well that you can adapt:

Clear, aggressive messaging

“Build enterprise software in days, not months.” Blitzy

“80%+ built autonomously, final 20% codified for your engineering team.” Blitzy

“Infinite code context”, “System-2 AI”, “3,000+ agents”.

→ For ConnectSoft, you can do:

“Build SaaS platforms in weeks, not quarters.”

“Standardized .NET / Azure SaaS foundations built autonomously; your team focuses on domain specifics.”

“Factory-grade DDD & event-driven architecture baked into every service.”

Enterprise-grade pricing & packaging

They’re not shy: $50K concept, $250K pilot, $500K+ enterprise, $3M+ transformation.

→ For ConnectSoft you can have:

“SaaS Platform Launch Pack” (Identity + Audit + Config) at a serious, project-based price.

“Factory deployment + template customization” as a six-figure engagement.

You can still have lighter, low-ticket dev subscriptions later, but keep enterprise options on the table.

Strong story about validation / quality / benchmarks

They lean heavily on SWE-bench Verified, “System-2 reasoning”, validation at compile & runtime. PR Newswire

→ For ConnectSoft:

You have your own “quality levers”: DDD, templates, BDD/SpecFlow tests, test containers, OpenTelemetry.

You can construct internal benchmarks: e.g., time-to-service, bug rates, test coverage, incident comparison pre/post-factory.

Security & trust center

Dedicated security/compliance pages, SOC 2 Type II, “no training on your code”. Blitzy +1

→ You already think deeply about compliance. Just make sure connectsoft.ai / .io have very explicit:

Security posture

Data residency statements

“No training on your tenant data without explicit opt-in”

Future SOC2/GDPR roadmap

  1. Where You Can (And Should) Differentiate Hard

Here’s where ConnectSoft can be clearly not just “another Blitzy clone”:

Nail the “SaaS factory” vertical with strong SaaS primitives

Explicit first-class model for:

Tenant

Edition

Feature / quota

Billing hooks

Audit + configuration + identity as shared platform services

Blitzy is “autonomous enterprise dev” in general. You can be “autonomous SaaS platform dev” in particular.

Deep .NET + Azure + Clean Architecture specialization

Blitzy is pan-language and model-first.

You are stack-opinionated and can ship:

Ready-to-run microservice templates

Azure DevOps pipelines / Bicep / AKS manifests

NHibernate / MassTransit / OpenTelemetry patterns

That makes ConnectSoft extremely attractive to any .NET/Azure-centric shop that wants not just code, but a codified reference architecture.

Factory outputs = products on .io

You’re not only selling the factory; you’re shipping finished SaaS services (Identity, Audit, Config, Bot) from that factory and proving they work in production.

That gives you dogfooding + credibility: “All our own SaaS is built by the same factory you get access to.”

Planned marketplace & ecosystem

Templates, agents, connectors, microservices, vertical packs.

Potential to open to external partners domain-by-domain.

That’s a path to an ecosystem more like “app store for SaaS building blocks”, not just “one company’s closed platform.”

Domain-vertical depth

You already have strong veterinary, insurance, education/Kabbalah cases.

You can ship vertical SaaS modules:

Vet booking & medical record context

Insurance policy & claims context

Learning/bot infrastructure for education

Blitzy feels horizontal. You can be horizontal factory + vertical lines.

  1. Concrete Next Steps For You After Seeing Blitzy

If we translate this research into your roadmap:

Sharpen your messaging:

On connectsoft.ai, very explicitly say:

“AI software factory for multi-tenant SaaS on .NET & Azure.”

“Generates architecture, microservices, infra, and docs – not just code.”

Use strong, direct lines similar in energy to Blitzy, but with your SaaS angle.

Define 2–3 flagship verticals

E.g.:

“Identity & Access Platform”

“Audit Trail Platform”

“External Configuration Server”

On connectsoft.io, make them as polished as Blitzy’s “platform overview” pages.

Plan your own “enterprise plans”

Short version:

ConnectSoft Factory Pilot: €XXk, N microservices, Y weeks.

SaaS Platform Launch Pack for Identity+Audit: €XXk, including onboarding and customizations.

Long-term: subscription + support.

Codify your differentiation points in a comparison slide

Internally, make a table:

Dimension Blitzy ConnectSoft Factory Primary focus Any enterprise code Multi-tenant SaaS platforms Stack Language-agnostic Opinionated .NET / Azure Unit of value LOC generated / refactored Running SaaS platforms + templates SaaS primitives Not explicit Tenants, editions, features, quotas Outputs Repos + docs Repos + infra + observability + docs Marketplace Not public yet Planned (templates, agents, modules)

This becomes useful for investors, partners, and your own focus.

If you want, next I can:

Draft a “Blitzy vs ConnectSoft” internal memo/pitch in markdown you can keep in your strategy repo, or

Rewrite your one-page ConnectSoft value prop explicitly positioned in the “same category as Blitzy, but for SaaS / .NET / Azure and platform products”.

I said: I also have connectsoft.co.il domain

Nice, that one is actually a super valuable asset for you.

You now have:

connectsoft.ai – global AI factory brand

connectsoft.io – global SaaS products catalog / actual platforms

connectsoft.dev – global dev/docs hub

connectsoft.co.il – Israel-specific presence

Here’s how I’d use connectsoft.co.il without creating chaos.

  1. Main Role of connectsoft.co.il

Use it as your Israeli-facing site in Hebrew, focused on:

Freelance/consulting work

Architecture & AI factory services for local companies

Case studies of Israeli clients

Local contact details, pricing options, legal stuff if needed

Think:

“דף הבית של ConnectSoft לשוק הישראלי – פתרונות SaaS, פלטפורמות AI, וייעוץ ארכיטקטורה.”

So:

Global narrative, English → connectsoft.ai / .io / .dev

Local narrative, Hebrew → connectsoft.co.il

You can still mention the factory & products, but framed as services you bring to Israeli clients.

  1. Concrete Structure for connectsoft.co.il

Very light, focused site:

Home (Hebrew)

Who you are (דימה / דימיטרי, ארכיטקט תוכנה, CTO חיצוני וכו’)

What ConnectSoft offers:

בניית פלטפורמות SaaS מרובות דיירים (.NET + Azure)

פיתוח ובניית AI Bots ו-AI Factory

אינטגרציות (Vetspire, Greenhouse, Braze, Talkdesk, וכו’)

Short “why work with me/us” section

Services

ייעוץ ארכיטקטורה ו-CTO חיצוני

הקמת פלטפורמות SaaS במודל multi-tenant

בניית בוטים חכמים, AI Agents ومערכות Agentic

אינטגרציות ענן ו-Data Pipelines (Azure, Snowflake, וכו’)

Solutions (links to global)

Identity / Audit / Config / Bot → with short Hebrew explanation + link:

“קרא עוד באתר הבינלאומי” → connectsoft.io

“קרא על ConnectSoft AI Factory” → connectsoft.ai

About & Contact

פרטים עליך

דרכי קשר (טלפון, מייל, וואטסאפ)

אולי טופס לידים קצר

You don’t need a huge site – 1–3 pages in Hebrew is enough to have a proper local face.

  1. How It Connects to .ai / .io / .dev

I’d keep the roles very clear:

connectsoft.co.il – “שלום, אני ConnectSoft בישראל.”

Hebrew

Consulting & services

Links out to .ai / .io / .dev for deep technical/product info

connectsoft.ai – “Here is the global AI factory story.”

connectsoft.io – “Here are the ready-made SaaS platforms (products).”

connectsoft.dev – “Here’s how to use & integrate everything (developers).”

So your flow for an Israeli lead is:

see you on LinkedIn → click connectsoft.co.il → understand what you do in Hebrew → click through to .ai / .io if they want more depth.

  1. DNS / Routing Recommendation

Simple setup:

connectsoft.co.il → dedicated simple Hebrew landing site (can be Webflow / static)

Optionally:

www.connectsoft.co.il → same landing

/en path to redirect to connectsoft.ai if someone wants English

No need for extra subdomains under co.il for now.

  1. TL;DR

Don’t use .co.il for the factory or products themselves. Keep those on .ai and .io as planned – global, English, technical.

Use connectsoft.co.il as your Israeli business front in Hebrew, focused on:

Your freelance / consulting / architecture role

Local services powered by the ConnectSoft factory & platforms

Links to .ai / .io for deeper info

If you want, next step I can draft full Hebrew homepage copy for connectsoft.co.il (headline, sections, bullets) that you can paste into Webflow or any builder.

I said: Let's continue with business and pricing models for example employment services where which customer can select and "hire" agents, 3 developers, one DevOps,2 product managers etc

Love this direction – you’re basically talking about “AI Team-as-a-Service”: instead of hiring humans, the customer configures a virtual team of agents (3 “devs”, 1 DevOps, 2 PMs, etc.) and pays for its capacity.

I’ll break it into:

How to frame this offering

Business model patterns that fit

Concrete pricing models for “hire N agents”

How this plugs into your ConnectSoft universe

  1. What You’re Actually Selling

Not “employment” in the legal sense, but:

A managed, virtual product team composed of specialized AI agents (plus some human oversight) that builds and maintains SaaS components for the customer.

Example “team”:

1 Architect Agent (blueprints, DDD, context maps)

3 Dev Agents (backend microservices, libraries, frontend modules)

1 DevOps Agent (CI/CD, infra, observability)

1 QA Agent (tests, BDD, quality gates)

1 Product/PM Agent (requirements, user stories, scope tracking)

The customer doesn’t own employees; they get capacity and outcomes from that virtual team.

So we need business/pricing models that are:

Easy to understand (“this behaves like a squad you hired”)

Safe for you (no unlimited scope traps)

Mapped to outputs and usage, not just “hours”

  1. High-Level Business Model Patterns

You can mix several of these:

A) “Squad Subscription” – Virtual Team Retainer

Customer rents a configured agent squad per month.

They choose:

Roles (e.g., Architect, Dev, QA, DevOps, Product)

Capacity level (Small / Medium / Large squad)

You commit to:

A certain throughput per month (e.g., “up to 2 new microservices + maintenance”)

Response times / SLA for changes & fixes

Charged as monthly subscription, with minimum term (3–6 months).

This feels most like “employment services” and easiest to sell to CTOs and heads of product.

B) “Outcome-Based Packages”

Instead of “3 dev agents + 1 devops”, you sell packages:

“New SaaS Service Package”

“Integration Package (Greenhouse → Braze style)”

“AI Bot Launch Package”

Each package internally uses a squad of agents, but the customer buys outcome:

Package has:

Defined scope (features, integrations)

Expected delivery window

Fixed or semi-fixed price

This can sit on top of the squad model as a more productized offering.

C) “Usage-Based Agent Credits”

Treat agents more like cloud services:

Customer buys Agent Credits (e.g., 10k credits/month).

Each agent action has a cost:

“Blueprint generation run” = X credits

“Microservice scaffold + tests” = Y credits

“CI/CD pipeline generation” = Z credits

You show them usage dashboards: “your 3 Dev Agents consumed 8k credits this month.”

Good for advanced customers, but harder to explain to normal business people. I’d keep this as an optional, advanced mode.

D) “Hybrid Staff-Aug” (AI + Human Hours)

For some clients, you blend:

Virtual squad of agents

Reserved human architect / engineer hours per month

Model:

Base subscription: AI squad

Add-on: N hours of “senior architect review” or “pairing with your team”

This bridges the trust gap: they feel they still “have a human” to talk to.

  1. Concrete Pricing Models for “Hire Agents”

Let’s turn your example (“3 developers, 1 DevOps, 2 PM/product agents”) into something structured.

3.1 Don’t price per agent like humans

If you say “3 Dev Agents = X € each”, you’ll get trapped in weird expectations (“I want them 8 hours/day…”).

Instead, price bundles that internally translate to agent capacity.

3.2 Example: Squad Tiers

Define 3–4 standard squad configurations:

1) SaaS Starter Squad

For startups / MVPs.

1 Architect Agent

2 Dev Agents

1 QA Agent

0.5 DevOps Agent (shared)

0.5 Product Agent (shared)

Delivers per month (example):

Up to 1 new microservice (full template, APIs, tests, infra)

Up to 2 feature epics in existing services

Ongoing bugfixes for what the squad created

Basic CI/CD & monitoring

Pricing model:

Fixed monthly subscription

3-month minimum

Overages if they exceed scope (more epics or services)

2) SaaS Growth Squad

For teams scaling from MVP.

1 Architect Agent

3 Dev Agents

1 QA Agent

1 DevOps Agent

1 Product Agent

Delivers per month (example):

Up to 2 new microservices

Up to 4 feature epics

1 major integration (e.g., new third-party API)

Enhanced observability & performance tuning

Pricing model:

Higher monthly subscription

6-month minimum, includes periodic architecture reviews

3) Platform Squad (Enterprise)

For organizations building internal platforms.

1 Senior Architect Agent

4 Dev Agents

2 QA Agents

1 DevOps Agent

1 Governance/Compliance Agent

1 Product Agent

Delivers per month (example):

New platform capabilities (identity, audit, config, bot, etc.)

Cross-cutting features applied across multiple services

Governance policies & templates (for their dev teams)

Pricing model:

Premium monthly retainer

Possibly combined with usage-based pricing on top (for heavy generation runs)

3.3 “Agent Configurator” You Described

You can still offer a “Build your squad” UI:

“Pick 3 Developer Agents, 1 DevOps Agent, 2 Product Agents…”

But in the backend you should map combinations to pre-defined pricing bands, e.g.:

Small Team (up to X “agent units”)

Medium Team

Large Team

Where each role has an internal weight:

Dev Agent = 1 unit

DevOps Agent = 1.2 units

Architect Agent = 1.5 units

Product Agent = 0.8 units

QA Agent = 0.8 units

So 3 Devs (3) + 1 DevOps (1.2) + 2 PMs (1.6) = 5.8 units → falls into “Medium Team” tier.

Customer sees: nice price tier. You see: predictable cost/throughput expectations.

3.4 Tie Pricing to Outputs, Not Just Capacity

To avoid being “just another outsourcing shop”, every plan should include output guarantees:

Examples:

“We commit to delivering up to N new services or M feature epics / month, subject to complexity.”

“We always include tests, docs, and observability wiring.”

“We maintain what we build while you’re subscribed.”

You can have variable add-ons:

Extra microservice beyond plan capacity

Extra integration project

Performance optimization sprint

  1. Where This Lives in Your ConnectSoft Universe

I’d position this as a fourth pillar:

connectsoft.ai – AI Factory (technology + console)

connectsoft.io – SaaS platforms (Identity, Audit, Config, Bot…)

connectsoft.dev – Developer/docs portal

teams.connectsoft.ai or workforce.connectsoft.ai – AI Squad / Employment-style service

Conceptually:

The Factory is the engine.

The Squads are managed configurations of agents running on that engine.

The Platforms are example outputs (your own products on .io).

On the teams site, you’d show:

Predefined squad types with pricing (Starter, Growth, Platform, Integration Squad, AI Bot Squad)

Configurator: “design your own squad” → maps to a plan

Case studies: “This Growth Squad delivered [X] microservices & integrations for Client Y.”

  1. Risk & Guardrails

To make this viable:

Scope control: Every squad has a clear monthly budget of “story points / features / microservices”. Extra work = upsell.

Transparency: Dashboards showing:

Which agents ran

What they delivered

Factory logs / traces for trust

Human oversight: Even if 90% is agentic, always present “Architect-in-the-loop” for high-risk customers (as part of plan).

  1. TL;DR

For “employment-style” services where customers choose “3 devs, 1 DevOps, 2 PMs”:

Don’t literally rent out single agents;

Bundle them into squad tiers with clear outputs and monthly subscription pricing.

Let customers configure squads through a UI, but map combinations to pre-priced tiers internally.

Offer:

Squad subscriptions (team-retainer)

Outcome packages (build a new microservice / integration)

Optional usage-based credits for power users

Hybrid plans with some human-architect hours.

If you want, next step I can:

Draft actual plan descriptions (like pricing page copy) for 3–4 “AI squads” you could list tomorrow: Starter SaaS Squad, Growth Squad, Platform Squad, Integration Squad.

I said: yes

Perfect 😄 Let’s write this like real pricing-page copy you can paste into a site like teams.connectsoft.ai (or a “Teams & Squads” section on connectsoft.ai).

I’ll give you:

A short intro section

4 ready-made squad plans with clear descriptions

An optional “Build Your Own Squad” section

A small note on add-ons / usage

You can later plug in real prices or keep it “Contact us for pricing”.

Section Intro – “AI Product Squads”

Title: AI Product Squads – Your Virtual Team, Powered by the ConnectSoft Factory

Subtitle: Choose a ready-made AI squad that behaves like a focused product team. Each squad is a managed group of specialized agents (architecture, dev, QA, DevOps, product) running on the ConnectSoft AI Software Factory. You get production-ready SaaS components, not just code.

Blurb: Instead of hiring and onboarding an entire team, you configure a virtual squad with the right mix of “roles” – developer agents, DevOps agents, architect agents, product manager agents, QA agents – and we deliver concrete outcomes every month: new microservices, integrations, features, tests, and infrastructure.

Plan 1 – Starter SaaS Squad

For MVPs and early-stage products that need a solid foundation, fast.

Tagline: Start your SaaS on the right architecture, without hiring a full team.

Who it’s for:

Startups and product teams building their first multi-tenant SaaS or core platform.

Companies that want an MVP with clean architecture, tests, and CI/CD from day one.

Squad composition (internal):

1 Architect Agent

2 Developer Agents

1 QA Agent

0.5 DevOps Agent (shared)

0.5 Product/PM Agent (shared)

What we deliver each month (example scope):

Up to 1 new microservice generated and wired (Clean Architecture, DDD, REST API, tests, infra templates).

Up to 2 feature epics (e.g., new endpoints, domain logic, flows) in existing services.

Basic CI/CD pipelines and observability (logging, tracing, metrics) for the services this squad owns.

Documentation: feature specs, architecture notes, API docs for everything we build.

Ideal outcomes:

Launch a first version of your SaaS backend or a key platform component (e.g., billing, simple identity, reporting).

Have a codebase that your own developers can extend without hating you later.

Pricing:

Monthly subscription with a 3-month minimum.

[Button copy: “Talk to us for a Starter Squad quote”]

Plan 2 – Growth SaaS Squad

For teams that already have something running and need to ship more, faster.

Tagline: Scale your SaaS roadmap with a virtual team that ships new services and features every month.

Who it’s for:

SaaS companies post-MVP, adding new modules and integrations.

Teams that want to standardize on ConnectSoft templates and the AI Factory while continuing to move fast.

Squad composition (internal):

1 Architect Agent

3 Developer Agents

1 QA Agent

1 DevOps Agent

1 Product/PM Agent

What we deliver each month (example scope):

Up to 2 new microservices built from ConnectSoft templates (multi-tenant ready, event-driven, observability-first).

Up to 4 feature epics across existing services (new flows, refactors, performance improvements).

1 major integration with a 3rd-party API or internal system (e.g., payment provider, CRM, ATS).

Upgrades to CI/CD, monitoring, and resilience for the services under this squad.

Updated documentation and ADRs for all significant decisions.

Ideal outcomes:

Expand your platform with new capabilities (e.g., Audit Trail service, External Config, Notification module) without spinning up a new in-house team.

Keep architecture consistent across all new services.

Pricing:

Monthly subscription with a 6-month minimum commitment.

[Button: “Schedule a Growth Squad consultation”]

Plan 3 – Platform Squad (Enterprise)

For organizations building internal platforms and large multi-product SaaS ecosystems.

Tagline: An AI-powered platform team dedicated to your internal SaaS platform and shared services.

Who it’s for:

Enterprises and scale-ups building an internal platform (identity, audit, config, messaging, shared services).

Organizations with multiple product teams that need a stable, opinionated backbone.

Squad composition (internal):

1 Senior Architect Agent (platform-level)

4 Developer Agents

2 QA Agents

1 DevOps/SRE Agent

1 Governance/Compliance Agent

1 Product/Platform PM Agent

What we deliver each month (example scope):

New platform capabilities and shared services (e.g., Identity Platform enhancements, Audit Platform, External Config improvements, shared domain services).

Cross-cutting features rolled out across multiple services (e.g., new auth flows, tracing improvements, data retention policies).

Governance artifacts: architectural standards, templates, golden paths for your internal teams.

Continuous hardening: security, performance, resilience, multi-tenant isolation checks.

Deep documentation for platform usage, integration guides, and internal SLAs.

Ideal outcomes:

Your internal teams build on top of a stable, well-governed platform instead of reinventing the basics.

The ConnectSoft Factory becomes the engine that keeps your platform evolving safely.

Pricing:

Premium monthly retainer (often part of a broader enterprise agreement).

[Button: “Discuss a Platform Squad engagement”]

Plan 4 – Integration & AI Bot Squad

For companies that need integrations + AI around their existing systems.

Tagline: Specialized in stitching your systems together and layering AI on top.

Who it’s for:

Teams needing integrations like “Greenhouse → Braze”, “Vetspire → Data Platform”, “CRM → Marketing”.

Businesses wanting to add AI bots and assistants on top of existing data (support, internal tools, knowledge bots).

Squad composition (internal):

1 Integration Architect Agent

2 Developer Agents (APIs, ETL, functions)

1 AI/ML Agent (prompts, flows, RAG)

1 QA Agent

0.5 DevOps Agent

0.5 Product Agent

What we deliver each month (example scope):

Up to 2 integration/data pipelines (e.g., Greenhouse → Braze, Vetspire → Snowflake, Segment → Mixpanel).

Design and implement AI bots:

Connecting to your systems via APIs

Using your data for context (RAG, embeddings)

Integrating with channels (web, chat, Teams/Slack, etc.)

Observability and error tracking for all integrations and bot flows.

Documentation: data contracts, integration diagrams, bot behavior specs.

Ideal outcomes:

Stop doing glue work manually – have an AI squad that owns integrations and bot capabilities as a first-class product.

Your team focuses on core product, not plumbing.

Pricing:

Monthly subscription with optional project-based add-ons for large integration programs.

[Button: “Plan your integration & AI roadmap with us”]

“Build Your Own Squad” (Configurator Concept)

Title: Custom Squad – Configure Your Own Virtual Team

Blurb: Need something more specific? Configure your own squad by choosing the mix of agents you want: Developer, Architect, QA, DevOps, Product, Governance, AI/ML. We’ll map your configuration to a capacity tier and agree on concrete monthly outcomes.

How it works (visible to customer):

Choose roles & intensity:

Developer Agents: 1–5

Architect Agents: 0–2

QA Agents: 0–3

DevOps Agents: 0–2

Product/PM Agents: 0–2

Optional Governance/AI Agents

Define your goals:

New microservices / month

Feature throughput (epics / month)

Integrations / AI features

We propose:

A capacity tier (Small / Medium / Large) matched to your configuration.

A clear scope per month and subscription price.

CTA:

“Build your squad →” (leads to a short intake form or interactive configurator later)

Add-ons & Usage (Optional Section)

You can add a short section for upsells/additional levers:

Title: Add-ons & Usage-Based Options

Extra Microservice Need more than your squad’s monthly quota? Add extra fully generated, tested microservices for a fixed add-on fee.

High-Throughput Mode Temporarily boost your squad’s capacity (e.g., product launch) with extra Developer/QA/DevOps agent cycles.

Human Architect-in-the-Loop Add reserved human architect hours per month for reviews, workshops, and live collaboration with your team.

Factory Access For advanced customers, we can grant direct access to parts of the ConnectSoft AI Software Factory so your own engineers can trigger agents and templates.

If you want, next step I can:

Turn this into a single pricing page layout (with headings, “cards”, and button labels exactly as in real HTML/Markdown), or

Draft the Teams & Squads section for connectsoft.ai including a short explanation diagram of how “Squad → Factory → SaaS components” flows.

I said: What about platform code it's open or closed? Generated code? As you know factory integrated with azure DevOps and create and manage code,work items, artifacts, pipelines etc

Great question – this is exactly the kind of thing you want clear before you start selling Factory + squads.

Let’s separate:

What “kinds” of code you have

Who should own what (IP model)

How this plays with Azure DevOps integration

Concrete recommendation for ConnectSoft

  1. You actually have 4 distinct code layers

It helps to think in layers instead of “open or closed” as one big switch:

Factory Runtime (Core Platform)

Orchestrator, agent host, schedulers

UI/console (projects, runs, logs)

Internal services: knowledge store, vector index, policy engine, etc.

Agent orchestration logic, planning, evaluation.

Templates & Libraries (what agents use to generate things)

Microservice templates (ConnectSoft.MicroserviceTemplate)

Library templates (ConnectSoft.Extensions.*)

Frontend templates, DevOps templates (pipelines, Bicep, etc.)

Agent blueprints (prompts, policies, workflows)

ConnectSoft Product Code

Identity Platform code

Audit Trail Platform code

External Config Server code

Bot Platform code

Any “off-the-shelf” SaaS that you host under connectsoft.io.

Customer-Generated Assets (via Factory)

Customer’s microservices, libraries, frontends

Customer-specific pipelines, infra scripts

Work items, specs, tests, docs created in their Azure DevOps

Any derived code committed into their repos

Each of those can (and should) have different licensing/ownership rules.

  1. Ownership & openness – recommended baseline A. Factory Runtime – closed-source, proprietary

This is your core IP.

Don’t open the orchestrator, the control plane, or your agent runtime.

Offer it as:

Hosted SaaS (you run it)

Or enterprise on-prem/self-hosted under a commercial license

Think of it like GitHub Copilot / JetBrains / HashiCorp – proprietary core.

Principle: customers can use the Factory, but not fork or resell the Factory itself.

B. Templates & Libraries – strategic mix of open & closed

This layer is your biggest lever for adoption.

I’d split it:

1) Open / “Open Core” components

Open-source (permissive or at least business-friendly) parts that help adoption:

Base microservice template (without all premium plugins)

Core ConnectSoft.Extensions building blocks that are neutral:

Logging helpers

HTTP/OAuth2/OpenID client helpers

OpenTelemetry wiring

Basic DevOps pipeline templates (stripped-down versions)

Benefits:

Devs can see how things work.

Easier for external contributors / partners to extend.

Reduces “black box” fear.

2) Closed / commercial components

Keep some higher-value pieces proprietary:

Advanced templates (multi-tenant SaaS template, complex EDA setups)

Specialized vertical templates (Insurance BCs, VetCare BCs, etc.)

Premium libraries:

Compliance & redaction

Governance & policy-as-code

Advanced agent blueprints

You can bundle these into paid tiers or marketplace items.

Principle: Use open templates to boost trust and adoption, keep the “superpowers” and vertical accelerators as paid/proprietary content.

C. ConnectSoft Product Code (Identity/Audit/Config/Bot) – depends on model

Your platforms on .io can be:

SaaS-only (hosted “black box”)

Customer uses APIs & UI

Code is fully closed

This fits typical B2B SaaS

Open-core products

Core of Identity/Audit/Config might be public

Proprietary modules for:

Multi-tenancy hardening

Compliance features

Managed hosting / support

Similar to how some commercial open source vendors work

Self-hostable closed-source

Customer gets a compiled package or private repo via license

Code is closed, but they run it in their own Azure subscription

I’d recommend, at least initially:

Keep product code closed.

Offer:

Hosted SaaS on .io

Optional self-host license for enterprise (read-only repo or package)

You can always open some parts later if you see a community play.

D. Customer-Generated Code – always theirs (fully open to them)

This one is non-negotiable if you want enterprise trust:

Everything the Factory generates into the customer’s Azure DevOps is owned 100% by them.

That means:

The repos in their Azure DevOps org = their IP.

Generated C# microservices, tests, YAML pipelines, docs – all theirs.

They can:

Fork it

Modify it

Move it to GitHub/Bitbucket

Stop using your Factory and keep the code forever

Licensing-wise, you don’t impose any special restrictions on the output; your contract says something like:

“ConnectSoft retains IP in the Factory and templates. All code and artifacts generated into the Customer’s repositories belong to the Customer, except for any pre-existing ConnectSoft source or libraries referenced under their own licenses.”

Important nuance: they may reference your NuGet packages (e.g., ConnectSoft.Extensions.*), which remain under your package license. That’s normal: they own their code, you own your libs.

  1. How this plays with Azure DevOps integration

You already planned:

Factory connects to customer’s Azure DevOps org.

Factory:

Creates repos

Creates branches, PRs

Creates work items, tasks

Sets up pipelines, artifacts, etc.

From an ownership perspective:

Repo location is the deciding factor:

If repo is in their DevOps → it’s their IP.

If repo is in your DevOps → it’s your product/template.

So:

Factory behaviour you want:

Customer projects

Always in the customer’s Azure DevOps organization / project.

Factory authenticates via PAT/service connection.

All assets generated in their org are automatically their property.

ConnectSoft templates & runtime code

Live in your Azure DevOps or GitHub.

Customers only reference them (NuGet, submodules, template packages).

Shared patterns:

Template code never “leaks” as raw copied code without license, unless that’s intentional (e.g., open template).

Where template code is actually written into their repo, it should carry:

License header / comment

Or be from the open-source portion.

Audit trail:

You can stamp commits made by Factory with a bot user (connectsoft-factory[bot])

But still in their org, under their control.

Messaging to customer: “Our Factory connects to your Azure DevOps. All the project code and work items it creates there are yours. We don’t lock you in at the code level.”

This is a huge selling point vs “low-code, closed platforms”.

  1. Putting it together – recommended ConnectSoft model

If I put all this into one clear decision set:

1) Factory Core (Runtime & Orchestration)

Closed-source

Licensed / SaaS

Your strongest proprietary IP

2) Templates & Libraries

Base templates & some libraries: open-source (MIT/Apache 2)

Encourages adoption

People can play with ConnectSoft-style architecture even without full Factory

Advanced / vertical templates & libs: proprietary

Sold via plans or marketplace

“Pro SaaS Template Pack”, etc.

3) Platforms on .io (Identity/Audit/Config/Bot)

Start as closed-source SaaS, with optional self-host license.

Later optionally move some parts to open core.

4) Generated Customer Code

Always owned by customer.

Stored in their Azure DevOps.

You only have usage rights as necessary for:

Running the Factory

Support/maintenance

(Specify this in Terms)

5) Marketplace items

Third-party templates / agents / modules:

Creator owns IP of the item

You license it to customers via marketplace terms

Revenue share model between you and the creator

  1. How to explain this on your site (simple language)

You’ll want one short “Code & IP” section on connectsoft.ai, something like:

Factory & platform – proprietary ConnectSoft software, provided as SaaS or licensed for self-hosting.

Templates & libraries – a mix of open-source and commercial components; open pieces live on GitHub, commercial ones are included in paid plans and marketplace packs.

Your generated code – everything the Factory creates in your Azure DevOps (repos, pipelines, work items, docs) belongs 100% to you. You can use, modify, or move it freely, with no vendor lock-in.

And a slightly more formal version in your Terms & Conditions / MSA (with a real lawyer, obviously).

If you’d like, I can next:

Draft a “Code Ownership & Licensing” page in clean Markdown (for MkDocs / website), or

Propose a simple open-vs-closed matrix for each ConnectSoft component (Factory, Templates, Libraries, Platforms, Generated Code) that you can paste into your internal strategy docs.

I said: For example some microservice generated from microservice template therefore code in microservice come to be open and customer can reuse just by coping it and create more similar microservices without pay

Yeah, this is exactly the “oh wait, they can just copy the code” moment that every template / factory product hits. Short version: yes, they can copy it – and that’s OK as long as you design your business model and architecture around that reality.

Let’s break it down very concretely.

  1. Reality check: once code is in their repo, you can’t technically stop copying

If a microservice is generated from ConnectSoft.MicroserviceTemplate and lands in their Azure DevOps:

They can duplicate that repo.

They can create MicroserviceA, MicroserviceB, MicroserviceC by copy-paste.

They can even remove your factory entirely and still keep the code.

So you should assume:

Generated code = theirs. You can’t rely on “no copying” for revenue.

Trying to prevent reuse at the code level leads to ugly DRM-ish patterns and will scare serious customers.

So the trick is: make copying the code not the same as “having ConnectSoft”.

  1. Separate “what they own” from “what you sell”

Think in layers for each generated microservice:

Their Microservice Code (scaffold + business logic)

Controllers / endpoints

Application services / handlers

Domain model (entities, aggregates, value objects)

Tests → This should be 100% theirs. They can copy, fork, rename, etc.

ConnectSoft Packages & Runtime Pieces

ConnectSoft.Extensions.* NuGet packages

Special infrastructure modules (multi-tenancy, compliance, messaging, etc.)

Any “smart” libraries that hide complexity → These remain your IP, licensed like any normal library.

Templates & Factory Intelligence

The logic that decides what to generate, how to structure bounded contexts, which patterns to apply, how to wire everything together, how to create pipelines & work items → This is your differentiator, not the final C# files.

So even if they copy the microservice, what they don’t get by default is:

New versions of templates with improvements

Advanced / vertical templates they haven’t paid for

Agent orchestration logic

Knowledge graph, patterns, governance agents

Auto-generation of docs, tests, pipelines, work items

  1. Licensing & openness: concrete options

You have a few knobs you can choose from; you don’t have to pick only one.

Option A – Accept reuse of the scaffold: value is in Factory + advanced libs

Attitude:

“Yes, you can copy the basic microservice pattern. That’s fine. You’re paying us for speed, consistency, advanced templates, integrations, support, and hosted platforms, not for a single boilerplate service.”

This is basically open-core thinking:

Open-ish: base microservice layout, simple patterns.

Paid:

Multi-tenant features (editions, quotas, cross-tenant isolation checks).

Complex infra patterns (Chaos, multi-region, advanced messaging).

Compliance (audit, retention, redaction).

Specialized vertical templates (Vetcare, insurance, etc.).

The Factory itself and its agents.

Copying the basic hexagonal/clean skeleton is not a huge loss. Everyone can do that anyway.

Option B – Commercial license for templates (source-available, not open-source)

You can say in your license:

Customer may freely use the template-generated microservice code for their own systems.

But they may not:

Use the template to build a competing SaaS factory/template product.

Redistribute templates/libraries as a product.

Resell “ConnectSoft-based templates” without agreement.

This is enforced legally (MSA / EULA), not technically.

On the code side, you can:

Add a small license header comment in template-derived files.

Keep core logic in NuGet packages, so the “secret sauce” is not just static code.

Option C – Push more complexity into libraries, less into generated code

Architecturally:

Template-generated microservice:

Very thin wiring around controllers, handlers, and domain code.

Heavy lifting (cross-cutting, multi-tenant handling, infra glue) done via ConnectSoft.* libraries.

If they copy the service, they still depend on your packages for:

Tenant resolution, edition rules

Event publishing & subscription

Audit & logging behavior

Security and compliance behaviours

So yes, they can clone a microservice – but:

Upgrades & bug fixes live in your NuGets.

They can’t trivially “fork away” unless they reimplement all that complexity.

This also gives you a nice commercial hook: “You own the code; we maintain the platform libraries.”

  1. Why customers will still pay even if they can copy

Serious customers don’t want:

To maintain their own custom fork of a template forever.

To manually craft each new microservice and pipeline from scratch.

To hack on critical multi-tenant / security / infra concerns alone.

They do want:

Factory acceleration

“Click → new microservice with DDD, events, CI/CD, monitoring, docs, work items, all aligned to our standards.”

Architectural safety & consistency

Apply the same patterns across 10–100 services without human fatigue.

Upgrades and fixes

New template version automatically used in next generation.

Bugs fixed once in ConnectSoft.Extensions and applied everywhere.

Support & guarantees

They can call you when something weird happens.

They have someone accountable for the pattern, not just their random copy.

Copying one microservice does not give them any of those.

For big orgs, “we’ll save $X by copying instead of subscribing” is almost always a false economy.

  1. Recommended ConnectSoft policy (pragmatic version)

If I had to write your internal rulebook:

Generated microservice code in customer repos

Fully owned by customer.

They can copy & adapt it freely inside their organization.

This is a selling point: “no lock-in at the code level”.

Core templates & base microservice skeleton

Either:

Open-source (MIT/Apache) → lean into adoption, or

Source-available with a commercial license that prohibits building a competing factory product.

Advanced templates & vertical patterns

Closed/commercial. Acquired via:

Factory subscription tiers, or

Marketplace packs.

ConnectSoft libraries (NuGet packages)

Normal commercial or OSS license (your choice).

Clear versioning and support policy (e.g., support only if you’re on a subscription).

Factory & agent system

Proprietary.

Access only via ConnectSoft SaaS or licensed on-prem deployments.

Contract language (non-lawyer version):

“Customer owns all artifacts generated into their repositories, except pre-existing ConnectSoft components (e.g., libraries, templates) which remain under their respective licenses.”

“Customer shall not use ConnectSoft templates and agents to build a competing commercial software factory or template marketplace, except as explicitly agreed in writing.”

Then you relax mentally about them copying the scaffold. You want that pattern to spread. Your value is:

Doing it at scale

Keeping it up to date

Embedding best practices

Providing platforms (Identity/Audit/Config/Bot) and squads on top.

If you’d like, I can next:

Draft a short “Code Ownership & Reuse” section you can put into your website (simple language) and a stricter internal legal note you can later hand to a lawyer to turn into MSA clauses.

I said: I want internally document this discussion and decisions and all future decisions,plans etc,let's plan structure

Perfect, this is exactly the right moment to formalize it before things explode 😄

Let’s design a lightweight but powerful “ConnectSoft Internal Playbook” structure that can live in a Git repo (MkDocs-ready) and grow with you.

I’ll split it into:

Types of docs you need

Recommended folder structure

Naming conventions for decisions (technical + business)

Where this conversation goes as concrete examples

  1. Types of docs you should have

Let’s distinguish 4 main artifact types:

Vision & Strategy Docs

Long-lived “how we see the world” and high-level plans.

Example: “ConnectSoft Product & Business Model Strategy 2025–2026”.

Playbooks & Reference Docs

Stable “how we do things” documents.

Example: “Domain & Subdomain Strategy”, “Code Ownership & Licensing Policy”.

Decision Records

Small, atomic documents capturing one decision each.

Both technical (ADR) and business (BDR).

Example: “BDR-0001 – Ownership of Generated Code”.

Roadmaps & Plans

Time-based: cycles, phases, releases.

Example: “Marketplace Roadmap”, “AI Squads Pricing Rollout”.

Everything in this conversation falls into 3 & 2: decisions + playbooks, fed by strategy docs.

  1. Recommended repo / docs structure

Assume a dedicated repo like connectsoft-internal or a folder in your main “Org” repo.

docs/ index.md

vision/ 00-overview.md 10-connectsoft-vision.md 20-product-portfolio.md # AI Factory, SaaS platforms, Squads, Marketplace

strategy/ 00-overview.md business-strategy.md # markets, segments go-to-market.md # .ai / .io / .dev / .co.il positioning pricing-strategy.md # high-level pricing principles marketplace-strategy.md # marketplace concept & phases

business-model/ 00-overview.md factory-business-model.md # .ai – licensing, usage, deployment options saas-platforms-model.md # .io – SaaS vs self-host, editions squads-business-model.md # AI squads/employment-style services code-ownership-model.md # templates vs products vs generated code

product-portfolio/ 00-overview.md ai-factory.md # product sheet for the Factory platforms/ identity-platform.md audit-platform.md config-platform.md bot-platform.md squads/ starter-saas-squad.md growth-saas-squad.md platform-squad.md integration-ai-squad.md marketplace/ templates-marketplace.md agents-marketplace.md modules-marketplace.md

domains-branding/ domains-overview.md # connectsoft.ai/.io/.dev/.co.il ai-domain-strategy.md io-domain-strategy.md dev-domain-strategy.md coil-local-site-strategy.md dns-subdomain-map.md # audit.connectsoft.io, console.connectsoft.ai, etc.

governance/ code-ownership-and-ip.md # legal/ownership rules security-and-compliance.md data-residency.md support-and-sla-policy.md

roadmaps/ 2025-roadmap.md factory-roadmap.md platforms-roadmap.md marketplace-roadmap.md squads-rollout-plan.md

decisions/ adr/ # Architecture Decision Records ADR-0001-factory-runtime-closed-source.md ADR-0002-microservice-template-architecture.md ... bdr/ # Business Decision Records BDR-0001-generated-code-ownership.md BDR-0002-saas-vs-self-host-model.md BDR-0003-domain-strategy-ai-io-dev-coil.md BDR-0004-ai-squads-pricing-model.md

meeting-notes/ 2025-12-11-business-model-session.md ...

You can expose some of this via MkDocs or keep it completely private/internal.

  1. Decision record templates (ADR + BDR) 3.1 Business Decision Record (BDR) template

File: docs/decisions/bdr/BDR-000X-some-title.md

BDR-000X –

  • Type: Business Decision
  • Status: Proposed | Accepted | Deprecated
  • Date: 2025-12-11
  • Owner: Dmitry
  • Related Areas: Business Model / Pricing / Factory / Platforms / Marketplace

Context

Short description of the situation that led to this decision.
What problem are we trying to solve? What options did we consider?

Decision

Clear, one-paragraph decision statement.
Example: “All code generated into a customer’s Azure DevOps organization is owned by the customer, while ConnectSoft retains IP to templates and libraries used to generate that code.”

Rationale

Why this is the right decision: - Bullet 1 - Bullet 2 - Tradeoffs

Consequences

What this implies going forward: - Positive consequences - Negative consequences / risks - Follow-up work required

  • Links to strategy docs, ADRs, other BDRs
  • Links to meetings or notes

3.2 Architecture Decision Record (ADR) template

File: docs/decisions/adr/ADR-000X-some-title.md

ADR-000X –

  • Type: Architecture Decision
  • Status: Proposed | Accepted | Deprecated
  • Date: 2025-12-11
  • Owner: Dmitry
  • System: AI Factory | Identity Platform | Microservice Template | etc.

Context

Technical context and constraints.

Decision

The architecture choice, clearly stated.

Rationale

Why we picked this option over alternatives.

Consequences

Technical impact: - On code structure - On operations - On future changes / extensibility

Alternatives Considered

  • Alternative A – why not
  • Alternative B – why not

  • Where this conversation fits – concrete files to create

Let’s map today’s topics into docs:

4.1 Business & code ownership

Create:

docs/business-model/code-ownership-model.md

High-level description of:

Factory runtime closed.

Templates/libs mixed (open + proprietary).

SaaS platforms closed (with possible self-host license).

Customer-generated code = theirs.

docs/governance/code-ownership-and-ip.md

Policy-style text (more formal).

This will later inform your MSA / T&Cs.

docs/decisions/bdr/BDR-0001-generated-code-ownership.md

Decision: “Customer fully owns all generated code in their Azure DevOps; ConnectSoft owns Factory and templates.”

4.2 Domains & hosting strategy

Create:

docs/domains-branding/domains-overview.md

Summarize roles of .ai, .io, .dev, .co.il.

docs/domains-branding/dns-subdomain-map.md

Table like:

www.connectsoft.ai – Factory marketing

console.connectsoft.ai – Factory console

audit.connectsoft.io – Audit SaaS

identity.connectsoft.io – Identity SaaS

docs.connectsoft.dev – Dev docs

connectsoft.co.il – Hebrew/local site

docs/decisions/bdr/BDR-0003-domain-strategy-ai-io-dev-coil.md

4.3 Squads / employment-style business model

Create:

docs/business-model/squads-business-model.md

Explanation of:

AI squads as monthly subscription.

Output-based scope (microservices/epics).

Predefined squad types (Starter/Growth/Platform/Integration).

Option for custom squads.

docs/product-portfolio/squads/*.md

starter-saas-squad.md, growth-saas-squad.md, etc.

Use the pricing-page-style copy we just created.

docs/decisions/bdr/BDR-0004-ai-squads-pricing-model.md

4.4 Marketplace

Create:

docs/strategy/marketplace-strategy.md

Phase 1: internal only

Phase 2: private marketplace for big clients

Phase 3: public marketplace for templates, agents, modules.

docs/product-portfolio/marketplace/templates-marketplace.md docs/product-portfolio/marketplace/agents-marketplace.md docs/product-portfolio/marketplace/modules-marketplace.md

docs/decisions/bdr/BDR-0005-marketplace-phasing.md

  1. How to use this in practice

Day-to-day workflow:

After a big ChatGPT / whiteboard / meeting session like this:

Decide which decisions were actually made → capture as BDRs/ADRs.

Update or create strategy/playbook docs that reflect the decisions.

Drop meeting notes in meeting-notes/ if you want the raw history.

Once per week or cycle:

Scan recent BDR/ADRs.

Update any “overview” docs (e.g., business-model/00-overview.md) with links.

This way, the overviews stay readable, and the BDR/ADR folders hold the detailed history.

If you want, next step I can:

Generate actual skeleton files (content stubs) for the key docs we just listed so you can paste them into your repo and fill them progressively, or

Start with one fully written doc, for example: code-ownership-and-ip.md or domains-overview.md.

I said: Summary all conversation

Here’s a compact summary of everything we discussed in this thread about ConnectSoft, your factory, domains, business models, squads, IP, and internal docs.

  1. Overall Vision of ConnectSoft

ConnectSoft is:

An AI Software Factory for building opinionated, high-quality multi-tenant SaaS on .NET + Azure.

A provider of ready-made SaaS platforms (identity, audit, config, AI bots, etc.).

A potential AI squads / “virtual team” provider where customers “hire” agents (Dev, DevOps, PM, QA, Architect).

Core philosophy:

Clean Architecture, DDD, event-driven, cloud-native, observability-first.

AI agents + templates + DevOps deeply integrated with Azure DevOps (repos, work items, pipelines, artifacts).

  1. Domain Strategy: .ai / .io / .dev / .co.il connectsoft.ai – Factory & Vision

Role: AI Software Factory & control plane.

Content:

Vision, story, high-level architecture.

Factory product pages (what the Factory does, how it orchestrates agents).

Possibly a console (e.g. console.connectsoft.ai) and factory API (api.connectsoft.ai).

Use: Where you tell the story: “We build SaaS platforms with an AI factory.”

connectsoft.io – Ready-Made SaaS Platforms

Role: Catalog of ready-to-use SaaS solutions built with the Factory.

Examples:

Identity & Access Platform

Audit Trail Platform

External Configuration Server

AI Bot Platform

Structure:

www.connectsoft.io – marketing for these products.

Product subdomains (apps/APIs):

identity.connectsoft.io

audit.connectsoft.io

config.connectsoft.io

bot.connectsoft.io

Optionally app.connectsoft.io as a unified portal.

Tenancy patterns:

Tenant per path (audit.connectsoft.io/t/{tenant}),

or per subdomain (sploot.audit.connectsoft.io),

plus optional custom domains (e.g. audit.splootvets.com).

connectsoft.dev – Developer & Docs Hub

Role: Developer portal for:

Docs, APIs, SDKs, templates, guides, examples, roadmaps.

Structure:

www.connectsoft.dev – dev landing.

docs.connectsoft.dev – MkDocs-style docs:

Platforms (identity/audit/config/bot)

Factory (agents, flows, principles)

Templates & libraries

Guides and API reference

Changelog & roadmap.

connectsoft.co.il – Local Israeli Site

Role: Hebrew, Israel-focused front.

Present you (Dmitry) as architect/CTO-for-hire and ConnectSoft for local companies.

Explain services: SaaS platforms, AI bots, integrations, consulting.

Link out to .ai / .io for deeper technical/product information.

Simple 1–3 page site in Hebrew with services + contact.

  1. Product & Service Pillars

You effectively have 4 product lines:

AI Software Factory (.ai)

Multi-agent system that:

Generates microservices, libraries, infra, docs, tests.

Integrates with Azure DevOps (repos, work items, pipelines, artifacts).

Opinionated for multi-tenant SaaS, .NET, Azure.

SaaS Platforms (.io)

Identity & Access Platform

Audit Trail Platform

External Configuration Server

AI Bot Platform

Future platforms (reporting, notifications, etc.)

Offered as:

Hosted SaaS, and optionally

Self-hosted / licensed.

AI Product Squads (Teams of Agents)

“AI Team-as-a-Service” with configurable squads of agents:

Architect, Dev, QA, DevOps, Product, Governance, AI/ML.

You defined standard squads:

Starter SaaS Squad – 1 new microservice + 2 epics per month.

Growth SaaS Squad – 2 new microservices + 4 epics + 1 major integration per month.

Platform Squad (Enterprise) – builds shared platforms (identity/audit/config/etc.).

Integration & AI Bot Squad – data integrations + AI bots.

Subscription-based, tied to outcomes per month, not hours.

Future Marketplace

For:

Templates & blueprints

Agents & skills

Prebuilt microservices / vertical modules

Connectors & integration packs

Phased approach:

Phase 1: internal-only catalog.

Phase 2: private enterprise marketplaces.

Phase 3: curated public marketplace with revenue share.

  1. Business & Pricing Models

You explored several business model layers:

SaaS subscriptions (for .io platforms):

Per tenant, user, event volume, environments.

Tiers: Starter, Growth, Enterprise (self-host, SLAs, compliance).

Factory-as-a-Service / Platform Licensing:

Hosted Factory on your side.

Enterprise self-host license (on-prem / customer Azure).

Pricing:

By projects, seats, or usage (runs / generated artifacts).

AI Squads (virtual teams):

Monthly subscriptions for Squads with fixed capacities:

Defined in terms of “microservices/epics/integrations per month”.

Customer can configure a squad via a “team builder” UI, but internally:

Each role = unit weight.

Total units → mapped to a Small/Medium/Large tier with predefined pricing and output.

Marketplace revenue share:

Creators publish templates/agents/modules.

Customers buy via your platform.

Revenue share (e.g., 70/30) between creator and ConnectSoft.

Professional services & consulting:

Architecture, DDD, modernization projects.

Onboarding & customization for Factory and platforms.

Packaged offers: “Factory Launch Pack”, “SaaS Platform Launch Pack”, etc.

  1. Code, IP & Licensing Model

We clarified a layered IP model:

Factory Runtime (core)

Proprietary, closed-source.

Orchestrator, agents runtime, console, internal services.

Provided as SaaS or licensed self-host.

Templates & Libraries

Mixed model:

Base templates/libraries: can be open-source or permissive to boost adoption.

Advanced/vertical templates: commercial, part of paid tiers or marketplace packs.

ConnectSoft libraries (NuGet packages like ConnectSoft.Extensions.*) remain your IP under their own licenses.

Product Code (Identity/Audit/Config/Bot)

Initially: closed-source platforms on .io.

Options:

Hosted SaaS.

Self-host licenses for enterprises (code or deployable package).

Later you can move parts to an open-core model if it makes sense.

Customer-Generated Code

All code, pipelines, docs that the Factory creates in customer’s Azure DevOps:

Owned 100% by the customer.

They can copy, fork, modify, move to another Git provider.

They may still depend on your libraries & templates; those remain under your license.

Practical stance on “copying templates”

Yes: customer can copy a generated microservice and spin more from it.

That’s acceptable and expected; your value is:

Factory automation & consistency.

Advanced templates and libs.

Upgrades, support, and platforms.

Legal layer:

Customer may use generated code freely for their systems.

They may not build and sell a competing factory/template product out of your templates, per contract.

  1. Internal Documentation & Decisions Structure

You want to internally document all of this (and future decisions). The proposed structure:

Repo structure (MkDocs-friendly) docs/ index.md

vision/ 00-overview.md 10-connectsoft-vision.md 20-product-portfolio.md

strategy/ business-strategy.md go-to-market.md pricing-strategy.md marketplace-strategy.md

business-model/ factory-business-model.md saas-platforms-model.md squads-business-model.md code-ownership-model.md

product-portfolio/ ai-factory.md platforms/ identity-platform.md audit-platform.md config-platform.md bot-platform.md squads/ starter-saas-squad.md growth-saas-squad.md platform-squad.md integration-ai-squad.md marketplace/ templates-marketplace.md agents-marketplace.md modules-marketplace.md

domains-branding/ domains-overview.md ai-domain-strategy.md io-domain-strategy.md dev-domain-strategy.md coil-local-site-strategy.md dns-subdomain-map.md

governance/ code-ownership-and-ip.md security-and-compliance.md data-residency.md support-and-sla-policy.md

roadmaps/ 2025-roadmap.md factory-roadmap.md platforms-roadmap.md marketplace-roadmap.md squads-rollout-plan.md

decisions/ adr/ ADR-0001-factory-runtime-closed-source.md ADR-0002-microservice-template-architecture.md ... bdr/ BDR-0001-generated-code-ownership.md BDR-0002-saas-vs-self-host-model.md BDR-0003-domain-strategy-ai-io-dev-coil.md BDR-0004-ai-squads-pricing-model.md

meeting-notes/ 2025-12-11-business-model-session.md

Decision record types

BDR (Business Decision Record) – one business decision per file:

Context → Decision → Rationale → Consequences → Related.

ADR (Architecture Decision Record) – one technical decision per file:

Context → Decision → Rationale → Consequences → Alternatives.

You’ll capture things like:

BDR: “Customer owns generated code; ConnectSoft owns Factory & templates.”

BDR: “Domain strategy for .ai / .io / .dev / .co.il.”

BDR: “AI Squads as monthly subscription with outcome-based scope.”

ADR: “Factory runtime closed-source.”

ADR: “Microservice template structure (Clean Architecture, DDD, etc.).”

If you want, next step I can turn this into a ready-to-commit vision/20-product-portfolio.md + business-model/code-ownership-model.md based on this summary so you can drop them directly into your internal repo.

Extended thinking ChatG