Project case study
DevAssist
RAG-powered internal knowledge assistant. Answers engineering questions from docs, runbooks, and setup guides without pulling a senior engineer out of deep work.
Private implementation; details are shared at an architectural level.
Problem
- Engineers were losing real time to repetitive setup questions, docs lookups, and onboarding queries
- Every question pulled a senior engineer out of focus
- Knowledge was scattered across wikis, chat threads, and tribal memory
Constraints
- Answers must be grounded in verified documentation, not fabricated
- Everything must be editable and traceable
- Single interface for guided support, docs retrieval, and scaffolding, not a general chatbot
Architecture
- Documents chunked, embedded, and indexed for semantic retrieval
- Incoming questions matched against the knowledge base, relevant context injected into the LLM prompt
- Every answer cites its source documents
- Guided flows for the most common query types
Tradeoffs
- Retrieval-augmented over fine-tuning. Knowledge base changes weekly, retraining is not practical
- Guided flows over a single chat box. Most queries are repetitive and benefit from structured input
- Source-cited retrieval over freeform generation. Trust and traceability win
Outcome
- Repetitive support traffic dropped
- Onboarding got faster
- Senior engineers got hours of context-switching back each week