One index. Five ways to use it.

Ask who has dealt with a problem before, why a decision was made, or what was promised, and get the people and documents behind the answer.

One query across email, chat, docs, tickets and files, with every result linked back to where it lives.

Train a small open-source model on your own decisions and workflows, so it does one job better than the frontier, at a fraction of the cost, on hardware you control.

Sensitive content is masked as it is retrieved, so people and models only see what they are allowed to, without a separate redacted copy of your data.

Local agents run around the clock: they extract results, normalize vocabulary across teams, link related work and re-index as new files land.