This project explores how AI can be genuinely useful for engineering work when retrieval quality and system design are treated seriously.
Core idea
Instead of asking a model to guess, the system first retrieves relevant internal notes, documentation, or code fragments and then generates an answer grounded in that context.
What it focuses on
- fast document ingestion
- chunking and indexing strategy
- retrieval quality under noisy queries
- response latency and caching
- traceability of the returned answer
Why it is interesting
The hard part is not only generating answers. It is making the whole experience reliable enough that a developer would trust it during actual work.