AI answers with
receipts
Some professional questions can only be answered from a large, dense, constantly-changing body of specialist documents. Reading everything is impossible; guessing is expensive. General-purpose AI tools make the guessing faster, which is worse.
We built a system that answers only from the source material, and shows its working. Ask it a complex question and it returns an answer with citations pointing back to the exact passages it drew from, so a professional can verify every claim in seconds.
The corpus never sits still, so the system watches it: changes at source are detected automatically overnight, and ingesting an amended source is a reviewed step. The corpus and the test questions are withheld; the pattern is not.
Confident answers are easy.
Correct ones are not
Large AI models will answer any question you ask, fluently, whether or not they actually know. In casual use that is a quirk. In professional settings, where decisions carry real cost, an answer that cannot be verified is worthless, and a wrong one is dangerous.
The brief was a system where trust is structural: answers grounded in the source documents, every claim traceable to where it came from, and a knowledge base that tells you when a source has moved rather than waiting for someone to notice.
Every feature earned its place
Grounded answer engine
Built on Anthropic's Claude, with retrieval constrained to the corpus itself. Answers are generated from the source documents rather than from general model knowledge, with the sources presented alongside every response.
Citation-first design
Each answer links to the exact passages it drew from. Verification takes seconds, which is what makes the system usable professionally.
Automated corpus tracking
Changes to source documents are detected automatically overnight. Ingesting a new or amended source is a reviewed step, because a corpus that silently rewrites itself cannot be trusted.
REST API
The system plugs into existing tools and workflows rather than demanding another dashboard to log into.
Hardened dedicated infrastructure
Runs isolated on its own locked-down infrastructure, with the data going nowhere else.
Accuracy evaluation
Answer quality is measured against known-good test sets, so improvements are proven rather than felt.
Trust built into
the architecture
The engine is running against a live corpus that refreshes itself overnight, with the citation trail doing what no disclaimer can: letting the reader check the answer rather than trust it.
The pattern transfers to any document-heavy field. Contracts, regulations, technical standards, research libraries: wherever professionals drown in source material, an AI that answers with receipts turns reading time into decision time.