Sanciti RGEN
Most requirements live in developers’ heads, buried in legacy code, or scattered across meeting notes and Jira backlogs. RGEN extracts them automatically. It reads your codebase, documents, and conversations, then delivers structured BRDs, use cases, and test cases with full traceability. No manual tracing. No guesswork.
Faster documentation
Structured output types
Requirements traceability from source to story
How it works
RGEN takes in your legacy code, technical documents, meeting minutes and Jira stories, and turns them into eight structured output types: executive summaries, explicit and implicit specifications with their source content, object-level traceability, BRDs, auto-classification across functional, non-functional and technical categories, Jira-ready stories, SDLC traceability maps and real-time dashboards. AI use case generation and AI test case generation work together as a unified agentic requirement generator.
Ways to start
RGEN works with whatever you already have. Pick the starting point that fits your project.
Start by uploading your codebase as a ZIP file, or by connecting a Git, GitLab or Bitbucket repository. From there, the requirements document, the use cases and the technical analysis are built for you. And when the code moves on, just re-upload it: only the new and modified files are analyzed, so you’re not starting over.
Bring in a meeting transcript and get a summary, a requirements analysis and a stakeholder analysis. From those come a business requirements document with epics and user stories, plus Jira-ready items with acceptance criteria that map straight to your Jira and QTest fields.
No code to read? Start from technical and solution documents. They are analyzed on their own and produce the same requirements, use cases and reports.
Capabilities
Reads straight through your source code and finds the requirements, explicit and implicit, then packages them as audit-ready artifacts with full source-to-requirement traceability.
Takes what the code actually does and turns it into structured use cases and sequence diagrams, so engineering intent and business requirements end up speaking the same language.
Writes automated test cases and links each one back to the code and the requirements behind it, giving you full traceability and a more efficient QA process.
Remembers your codebase, naming conventions and domain terminology, so extraction gets more accurate with every engagement.
Advanced, portfolio and wave planning reports stay open. Add new analysis sections, regenerate them, and every earlier version is kept in the version history.
Portfolio analysis looks across the codebase at portfolio level. Wave planning analysis lays out the work in waves, so a large move can run in stages.
Just ask. Chat about a whole codebase, a single folder or a handful of files, and the answers come from your real project. Deep Scan takes more time, searching and checking files as it goes. When you have what you need, download the answers as Markdown or Word files, or save them to your storage.
Turn a prompt or a reference document into a reusable skill file. Apply it during analysis, and the output follows your template.
Regenerate or refine a single section of a report without redoing the rest.
Download any generated report in a structured format.
Analyze one file or one document on its own, without running the whole project.
Get the requirement specification as a JSON document, with epics and user stories.
Use cases
RGEN connects to GitHub, GitLab and Bitbucket for your code, to Jira and QTest fields for your stories, and to MinIO object storage for the documents it generates.
Deploy within existing workflows with no process disruption, immediate insight.
Agent Pipeline
RGEN is the starting point. Every downstream agent builds on the structured specifications and business rules it produces.
Extracts and structures requirements from any source
Runs autonomous tests to 90%+ coverage
Packages production-ready delivery bundles
Runs live production support after go-live
See RGEN in action
See how RGEN delivers audit-grade documentation from legacy code, meeting notes, and Jira backlogs, with full traceability from source to story, in a fraction of the time.
Full-service framework including:
Generates Requirements, Use cases, from code base.
Generates Automation and Performance scripts.
Code vulnerability assessment & Mitigation.
Production support & maintenance, Ticket analysis & reporting, Log monitoring analysis & reporting.
AI-Powered Legacy Modernization That
Accelerates, Secures, and Scales
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