DSGENAI - AI Safety Requirements Engineering Platform

DSGENAI is an AI-driven platform that helps engineers generate and work through requirements for safety-critical systems. By the time I joined it, the platform had outgrown its original Flask architecture: it was hard to maintain, awkward to use, and its question-generation logic was tied to a single use case. More seriously, it carried critical data-leakage issues that are unacceptable in a safety context.

The platform needed to become something the research team could rely on and extend - stable, maintainable, generalisable to new use cases, and running on a current model.

I stabilised and optimised the DSGENAI platform end to end. I migrated the architecture from Flask to Streamlit, which made the codebase far more maintainable and gave engineers a cleaner, more direct user experience for the requirements workflow.

I generalised the question-generation logic so a single, well-structured engine could serve multiple use cases instead of being hard-wired to one, and I tracked down and fixed the critical data-leakage issues so the platform behaved correctly and safely.

Finally, I integrated GPT-5.1 as the platform's model, improving the quality of the generated requirements output and bringing the tool up to a current, dependable standard for the team's research.