Knowledge and document systems

Start with the boundary. The library is defined, so the system reads what you cleared and nothing else. Every answer carries the document it came from, so a person can check it in seconds. And access rules are enforced inside the system, so a partner and a paralegal do not get the same answers to the same question when they should not.

Retrieval rules that require a source, and a graded evaluation set built before launch. We write questions with known answers, including questions the system should decline because nothing in the library covers them, and we measure it against both. A system that cannot find an answer should say so, and we test that it does.

Your firm does, collection by collection, and each collection gets a named owner. We run the inventory and put the contradictions in front of the owners, but the decision to include, exclude, or retire a document belongs to the person who is accountable for it. That is the whole basis of being able to trust an answer later.

Access is mapped before indexing, not bolted on after. The system runs inside your environment under your firm's existing permissions, and a document nobody should see is a document the retrieval layer will not return to them. Where a matter or client boundary applies, the library is partitioned along that boundary.

Each collection carries an owner and a refresh date. A person reads a sample of real answers on a schedule and flags anything that has drifted. Adding or retiring a document is a documented step your team performs, not a support ticket to us. This is the part most knowledge projects skip, and it is why they go stale.