[ INTERNAL_KNOWLEDGE ]
Grounded Answer Engine
What it is
A search box that returns a written answer with the sources it read.
[ THE_PROBLEM ]
Why this existed
Internal search returns a list of documents when the person wanted an answer. AI chat returns an answer when the person needed to know where it came from.
[ WHAT_WE_BUILT ]
What we built
A query triggers live retrieval, server-side page fetching and parsing, and a synthesis pass that writes an answer attributed to what it actually read — rather than returning ten blue links or an unsourced paragraph.
- Live retrieval triggered per query
- Server-side page fetching and HTML parsing
- Synthesis pass that writes an answer from what was actually retrieved
- Source attribution alongside the answer
[ HOW_IT_IS_USED ]
How a company uses it
Drop it in front of a support knowledge base or a public documentation set so staff and customers get an answer, plus the page to verify it against.
Built with
[ COMMON_QUESTIONS ]
Questions clients ask
How is this different from a standard chatbot?
A standard chatbot answers from what the model already knows, which may be outdated or invented. This retrieves current pages first and writes the answer from them, then shows you the pages. When the sources are thin, that is visible rather than hidden.
Can it run over our internal knowledge base?
Yes — the retrieval layer is the swappable part. Pointing it at an internal document set, a support knowledge base or a product catalogue instead of the open web is a straightforward change.
What happens when it cannot find an answer?
The honest behaviour, which we would insist on for any internal deployment, is to say so and show what it searched. An answer engine that confidently fabricates is worse than a search box.
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