[ Service — deep integration ]
AI at the core of your .NET estate
For mid-caps and software vendors whose IT lives in .NET and SQL Server: AI developed inside your application — document extraction, agents, classification — with your business rules, your architecture, your code. Not another tool next to the IT system: a new capability inside it.
This is for you if…
- Your IT system or product rests on a .NET / SQL Server estate that AI should enrich, not bypass.
- You're aiming for a native AI capability: document extraction, classification, business assistants — directly inside the application your users already know.
- Your context is demanding: industry, banking, healthcare, regulated environments — traceability and GDPR / AI Act compliance are non-negotiable.
- You have a technical team that wants a counterpart who can talk architecture, not just prompts.
What I deliver
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Document extraction in production
Scans and inbound documents turned into structured data: a swappable extraction engine (Azure Document Intelligence, Mistral OCR, Docling), business rules, transactional import.
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Agents integrated into the IT system
Semantic Kernel, Azure AI: agents that query your data and act inside your application, with your IT system's permissions and traceability.
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Clean architecture
Clean Architecture, DDD, tests: code your team can read, maintain and extend. Delivered in your repo, under your CI/CD.
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Full reversibility
No dependency on GiLabs: documentation, knowledge transfer, and abstractions that let you switch AI providers without a rewrite.
The process
The method of a serious software project, applied to AI — because that's what it is.
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Architecture review
Your IT system, your flows, your security and compliance constraints. We decide together where AI belongs and where it has no business being.
Deliverable: an architecture dossier validated by your technical team.
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Iterative development
Short sprints on your real data, code reviews with your team, quality measured at every iteration.
Deliverable: tested, deployable increments, in your repo.
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Production and handover
Deployment into your infrastructure, monitoring, documentation, training for the team taking over.
Deliverable: the AI capability in production, mastered by your developers.
Investment
This is the most committing tier — and the one that creates a durable asset: an AI capability your team owns, in code it masters, with no rent to pay to yet another vendor.
Investment
Fixed fee
Scoped in the architecture review, depending on integration depth. Scope, price and acceptance criteria agreed before the first line of code.