Most support bots either make things up or forward you to a human. This one answers only from documents it has actually indexed, and shows you which document each answer came from — running entirely on a local model.
A support assistant built on retrieval-augmented generation. Instead of relying on what a language model happens to remember, it retrieves the relevant passages from an indexed knowledge base first, then asks the model to answer using only that material — and reports the sources alongside the answer with a confidence score.
It ingests markdown, PDF and DOCX, and crawls the website on a nightly schedule so the index reflects the current site rather than a snapshot from whenever it was last built. Conversations are multi-turn, and questions it could not answer are logged as knowledge gaps — which is usually the most useful output for whoever maintains the documentation.
The failure mode that matters for customer support is not a missing answer — it is a confident wrong one. A model asked about refund terms it has never seen will still produce fluent text, and a customer has no way to tell the difference.
The second problem is staleness. A knowledge base indexed once drifts away from the live site immediately, and nobody notices until a customer is told something that stopped being true months ago.
Documents are split into passages and embedded into a vector index. A question is embedded the same way, the closest passages are retrieved, and only those are given to the language model as context. The answer carries the retrieved sources and a confidence score, so a low-confidence answer looks different from a well-grounded one.
The model runs locally through Ollama and the embeddings are open — there is no per-question cost and no document leaves the machine.
It can only answer from what has been indexed. Asked something outside the knowledge base it says so rather than guessing, which is the intended behaviour rather than a gap to close.
Answer quality tracks the local model. No accuracy benchmark is claimed — it has not been evaluated against a labelled question set, so no such figure appears anywhere.
The assistant is deployed here and answers from BitWithBite's own documentation. Ask it something the site covers, and something it does not.