Nitro Legacy Explorer: Legacy System Assessment

Teams that inherit a 10 to 15 year old business-critical system face the same recurring question: what else breaks if we touch this? Answering it usually means weeks of manual archaeology, and general-purpose LLM tools tend to answer confidently even when they are wrong.

Nitro Legacy Explorer binds code, BPMN processes, and the data model into one searchable knowledge layer. It combines a deterministic base, an AI-generated narrative, and human curation. The distinguishing property is verifiability: every statement points to a concrete location in the source, so a domain expert can check it in days rather than trusting a black box.

What the assessment delivers:

• A queryable knowledge layer over one customer-chosen module, expressed as YAML and Markdown.
• Impact analysis you can run in minutes instead of weeks.
• Output stored in the customer's own git repository. There is no lock-in: if you stop working with us, the knowledge layer stays yours.
• Living documentation that refreshes per pull request, so it stays current with the code instead of going stale.
• Connectable to existing tooling (GitHub Copilot, Cursor) through an MCP server, with output stored in the customer's own git repository. There is no lock-in: if you stop working with us, the knowledge layer stays yours.

What it deliberately is not: a one-click magic tool, a multi-year program, or shelf-ware documentation. The engagement is scoped, fixed, and tied to a single module you choose.

Built and delivered by Nitrowise Labs, an AWS Advanced Tier Partner. The approach has been applied to a Central European retail banking core.

AWS relation: This professional service relates to and drives usage of Amazon Bedrock, which powers the AI-generated narrative layer. The delivered knowledge layer runs in the customer's AWS environment and integrates with the customer's AWS-hosted repositories and development tooling.