Secure AI-assisted .NET modernisation: move to modern .NET without the IP risk.
.NET modernisation is a high-stakes transition: complex dependencies, legacy UI patterns and sensitive business logic. Artrilogic bridges speed and functionality with a security-first, AI-driven framework for enterprises that can't afford to leak IP into public models.
Three risks that should stop any enterprise from putting source code into a public LLM.
IP leakage
Uploading proprietary .NET source code to public cloud LLMs creates compliance exposure your security team will, rightly, refuse to sign off.
False progress trap
Public AI can generate syntactically correct code that fails at the architectural level due to missing context, passing tests while quietly breaking the system.
Dependency wall
Real .NET modernisation lives or dies on NuGet packages, runtimes and security postures that public models routinely mishandle.
Architectural alignment, sovereign AI infrastructure, intelligent decomposition.
Modernisation is a craft, not a script. The framework is what we use to turn a six-month roadmap into a matter of weeks, without sacrificing the things that matter.
Architectural alignment first
- Establish a Target State Architecture before any code is written.
- Intent preservation: capture business rules hidden in legacy event-driven behaviour.
- UI intelligence: transition ASP.NET Web Forms or MVC into modern Blazor or React with human-in-the-loop validation.
Private & air-gapped AI infrastructure
- Local, high-performance LLMs running on isolated multi-GPU infrastructure via Ollama.
- Zero data transit: code never leaves the secure environment.
- Sovereignty for regulated industries (finance, healthcare, government) with full data residency compliance.
Intelligent decomposition
- Proprietary slicing strategy that breaks monoliths into manageable, contextualised chunks.
- AI works with the reasoning behind the code, not just the syntax, dramatically reducing hallucination.
- 100% functional dependency graphs maintained throughout the migration.
Four phases. Honest checkpoints. No surprises.
Deep discovery & assessment
Map application dependency graphs and identify high-friction areas: custom UI components, legacy security providers, undocumented integrations.
Secure environment setup
Stand up a dedicated, offline AI instance tailored to your codebase's specific libraries, conventions and patterns.
Governed AI execution
Engineers guide the AI through migration in logical slices, validating against architectural goals, not just whether the compiler is happy.
Validation & hardening
Rigorous integration testing for performance, scalability and security against modern enterprise standards.
Decades of .NET. A practical view of AI.
We combine deep .NET experience with cutting-edge AI orchestration, and we're conservative about the things that actually matter, like your IP and your customers' data.
“The biggest risk isn't that AI writes bad code; it's that businesses mistake fast output for a safe strategy.”
What you get out of an assessment
- A dependency map of your current .NET estate
- A risk-ranked migration backlog
- A target architecture sketch for the modern stack
- An honest, time-boxed cost and timeline range
What enterprises ask before they commit.
Can we migrate directly from older .NET Framework (e.g. 3.5 or 4.5) to .NET 8/10?
Direct migration is possible but rarely straightforward. Older versions depend on deprecated libraries such as System.Web or legacy WCF configurations that have no direct modern equivalents. Our approach uses AI to identify friction points early, then architects modern alternatives (Minimal APIs, gRPC, EF Core) before migration begins, rather than discovering them mid-cutover.
How do you prevent our source code from being used to train public AI models?
We run local LLMs on air-gapped, private GPU infrastructure using the Ollama framework. Code never leaves the Artrilogic secure perimeter, ensuring complete data sovereignty and compliance with GDPR, HIPAA and SOC 2 expectations.
Why not just use the Microsoft .NET Upgrade Assistant?
The Upgrade Assistant works for simple projects but struggles with enterprise dependency graphs and complex architectural patterns. It moves code syntactically but doesn't analyse business logic. We use AI to refactor patterns, implement Dependency Injection and update Entity Framework 6 to EF Core: work the standard tooling flags but cannot resolve.
How does AI handle legacy UI like Web Forms or Silverlight?
UI conversion is where automation typically fails because rendering is tightly coupled to backend code. Rather than attempting blind conversion, we extract business intent from legacy components and map it to modern Blazor or React equivalents, preserving user experience while modernising the stack underneath.
What is the typical ROI on an AI-assisted migration?
Traditional manual migrations of enterprise applications take 12 to 18 months. Secure AI orchestration typically delivers a 40 to 60 percent reduction in timeline. ROI comes from accelerated delivery, reduced technical debt interest and earlier access to modern cloud-native performance.
Does your AI understand custom, in-house libraries?
Yes, using a Retrieval-Augmented Generation (RAG) approach inside the local environment. We ingest your internal documentation and library metadata so the AI understands proprietary frameworks and coding standards, ensuring migrated code aligns with your team's conventions.
Tell us about your .NET estate.
Share a few details and we'll come back within one business day with a proposed assessment scope.
Sovereign AI is one of the streams we watch as part of our forward research.