AI-Powered Modernization Framework

This isn't AI-assisted. It's AI-native.

The framework analyzes, modernizes, and documents legacy systems with AI agents – while senior engineers approve every gate. Built for environments where every change must be provable.

~2 hto analyze a codebase of 7,000+ files
194 pagesstructured analysis report, 33 sections
Line & SHAtraceability of every statement down to commit
100%human review at every gate
How it works

Four phases. Two of them are approved by no one but your engineers.

01 · AI AGENTS

Ingest

Full capture of code, docs, and dependencies. RAG-only – the model never gets direct filesystem access.

02 · AI AGENTS

Analyze

Structure, risk, and modernization analysis as an auditable report – the basis for scope and budget decisions.

03 · HUMAN GATE

Implement

AI-accelerated refactoring, test and doc generation. No merge without approval by senior engineers.

04 · HUMAN GATE

Maintain

Continuous modernization in operation – with an audit trail for regulators and internal audit.

Governance by design

No black box. Every parameter under your control.

The framework is built for architecture boards and compliance reviews – not around them.

  • RAG-only architecture – no direct filesystem or production access
  • Model-agnostic via MCP (incl. Claude, GPT) – no vendor lock-in
  • No customer data used in model training
  • Every statement traceable down to line and commit SHA
  • All autonomy parameters configurable – you define what AI is allowed to do
  • Operation with CH/EU data residency available
Architecture Deep Dive

For your architecture board: the complete technical documentation.

Reference architecture, integration paths into existing CI/CD and governance landscapes, autonomy-level configuration – and a list of what the framework cannot do.

Reference architecture CI/CD integration Autonomy levels L1–L5 Limitations Security model

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Case study

Java monolith with 20+ locales and audit columns – modernized AI-natively

Technical: full system analysis processed in ~2 hours instead of weeks. Business: a solid modernization scope as a budgeting and planning basis – before the first code change.

Read the whole case →

Frequently asked questions

Is AI-generated code allowed in a regulated production environment?

Yes – if every change is approved by qualified engineers and fully traceable. That is exactly what the human gates and commit traceability are built for.

Does the model get access to our source code?

Only via the controlled RAG layer, never directly to the filesystem or production systems. Customer data does not flow into model training.

Are we locked into a specific AI model?

No. The framework is model-agnostic via MCP; the model in use is configurable and replaceable.

For engineering & architecture

Technical demo

60 minutes on a real system: ingest, analysis report, gate mechanics, integration into your pipeline.

Book a demo
For transformation & business

Executive briefing

30 minutes of outcome and risk perspective: scope, cost-benefit logic, the regulator's view – no live tooling.

Request a briefing