RAG & Institutional AI
Institutional Knowledge Assistant, Islamabad
A retrieval-augmented assistant answering staff and public questions from approved documents.
- RAG
- Vector Search
- PostgreSQL
- Admin Panel
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Staff and the public asked the same questions repeatedly, and the answers lived across policy documents that nobody had time to search.
The work covered ingesting and chunking approved documents, semantic retrieval so answers stay grounded in the organisation’s own material rather than a model’s general training, and an admin layer so staff could maintain sources without developer involvement. Unanswered queries fall back to a named human contact rather than guessing.
What we built
- Document ingestion, chunking and semantic retrieval
- Answers grounded in approved source documents
- Admin interface for managing documents and FAQs
- Query logging and fallback to a human contact
- Deployment and handover documentation
Tell us what you're building.
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