Research archives
Index your documents, testimonies and books into queryable archives. Everything written is grounded in your sources — and the archive grows as the house works.
The failure mode of AI writing is confident invention. The fix is not a better prompt; it is giving the model something real to read. Research archives are that something.
Your material, indexed and queryable
Documents, transcripts, testimonies, reports, books — collected into named archives and indexed so they can be searched by meaning rather than by exact wording. A question phrased in your words finds the passage that answers it even when the passage uses different ones.
Personas read the archive as part of their work
Querying an archive is a tool like any other, which means a research step inside a routine can consult your sources before anything is drafted. The draft that follows is built on retrieved passages rather than recollection — and because the retrieval happened as a recorded tool call, you can see what it actually read.
The archive grows with the work
Material produced by the platform can go back into the archive, so a body of work compounds instead of scattering. What the house wrote last month is available to what it writes next month.
An archive is not a bigger context window. It is a body of sources that outlives any single conversation.
Access follows your rules
Archives live inside your organisation. Who can read one, and which personas may query it, follows the same permission system as everything else — so sensitive material can be present for the work that needs it and absent from the work that doesn't.
Where this pays off
Any writing that has to be defensible: legal and compliance summaries, historical work, research briefs, technical documentation, anything drawn from interviews. If someone might ask "where did that come from", the archive is the answer.