
Building a Grounded AI Recruiter Assistant with RAG and Semantic Caching
I built a recruiter-facing AI assistant that answers from my own notes and project history, not generic model confidence. The system uses retrieval, grounding checks, semantic caching, route metadata, and reliability checks to stay useful without pretending it knows things it cannot support.





