Plain language search across the documents your organisation actually runs on, with citations, permission awareness, and an honest answer when the material does not exist.
Search that returns an answer rather than a list of files, over content your team already wrote. It reads the documents, the prior work and the policies, and it tells you which document each sentence came from so you can check it.
Templates in a document system, decisions in email, context in chat, and the rest in the head of whoever did it last time. The information exists; the retrieval path does not.
Nobody searches for the filename. They ask what did we agree with this client about renewal terms, and the answer is spread across three documents that never use that phrasing.
An assistant that indexes everything and answers everyone will eventually surface a salary band, a board paper or a matter an associate should not see. Permission has to be enforced at retrieval, not filtered afterwards.
A policy superseded eighteen months ago reads exactly as authoritative as the current one. Without freshness and versioning, the assistant confidently tells your team how things used to work.
The parts that decide whether this survives contact with real data, real volume and real edge cases.
Access control is applied at retrieval time and inherited from the source system, so two people asking the same question get answers drawn from different documents. Nothing is filtered after the fact, because by then it has already been read.
Permission aware retrievalWe model the entities that matter to you, clients, matters, products, contracts, and the relationships between them, so a question about one surfaces the connected material rather than whatever shares vocabulary.
Knowledge graphAnswers are assembled only from retrieved passages, each linked to the document and location it came from. An unsupported claim cannot be produced, because there is nothing to attribute it to.
Citation enforced synthesisScanned PDFs, tables, appendices, inconsistent templates and twenty years of drift. Parsing, chunking and layout handling is most of the work, and it is the part that decides whether answers are any good.
Document processing pipelineIncremental sync as documents change, superseded versions demoted, and recency surfaced in the answer, so the assistant is not quietly quoting a policy that was replaced.
Freshness and versioningData residency, retention limits, no training on your content, and encryption in transit and at rest. For regulated work we can keep retrieval and inference inside your own cloud tenancy.
AI data protectionA 30 minute audit, no sales pitch. We map where this fits in your stack, what it would take to build, and whether it is worth doing at all.