engineering · 1 min read
Citations and Source Attribution: Building Trust in RAG Answers
Citations turn RAG from a confident hallucinator into a trustworthy assistant. Here is how Bhogar AI implements verifiable per-claim citations.
BABhogar AI TeamProduct & Engineering
A RAG answer without citations is a guess. A RAG answer with verifiable, per-claim citations is a tool a knowledge worker can actually trust. The difference is small in code and large in adoption.
Why it matters
Most teams either skip citations or bolt them on as a footer of "sources used". The right design is per-claim - every quantitative or factual sentence links to the chunk that supports it.
How Bhogar AI approaches it
Bhogar AI ships per-claim citation rendering, with click-through to the underlying chunk in the source document. The rendering layer works in chat, agent and document outputs across web and mobile.
- Per-claim citations with click-through
- Source highlighting in original PDF/HTML/Markdown
- Confidence score per citation
- "No source found" disclosure when retrieval is weak
- Citation export to Markdown, BibTeX and Notion
What you get
Adoption metrics on customer rollouts show 2-3× higher daily active usage when citations are visible by default versus hidden behind a "show sources" toggle.