Is this AI knowledge management, enterprise search, or RAG?
All three describe parts of it. Enterprise AI search is the front door, enterprise RAG (retrieval over your own documents) is one of the techniques underneath, and AI knowledge management is the whole system, one permissioned layer that people and agents query, with cited answers and a weekly brief on top. The difference from enterprise search software is that you own the layer and agents can act through it.
How is this different from Glean or Copilot?
Glean, Agentspace, and Copilot are strong products for search and summaries across the tools they connect, and if that covers your needs, buy one. We are not the right fit for a standard rollout with ordinary permissions. This is the alternative you own, modeled to your permissions and your workflows, with a brief built around your decisions, agents that act within limits you set, and the model underneath swappable as better ones ship.
Will it respect our permissions, and where does our data live?
Yes, structurally. Who can see each piece of information is recorded when it enters the system and enforced on every question, so a person or agent only ever gets back what their role could already see. The data and the system stay on your infrastructure or in your cloud tenancy, with nothing in a shared multi-tenant product, and retention follows your policy.
What about hallucinations?
Every answer carries citations to its source material, and when the system cannot cite a source, it says so. Claims trace back to the original message, transcript, or record, so anyone can challenge and verify an answer. As part of our alignment research, we study the ways an assistant goes wrong, like sycophancy and selective disclosure, and those findings shape how we build and test every knowledge management system.
Which model does it use?
A combination of frontier models by default, with the best fit chosen for each job. We build the system against evals, independent of any one vendor, so when a better model ships we can upgrade to it and prove the quality held. The same evals let you run open-weight models where you prefer them.
How long until it is useful?
The first slice of the knowledge management system is useful in weeks, because AE Studio starts it around one question your team keeps asking. It grows source by source from there, provided your security team grants read access to the sources and someone on your side owns the decision. Without those two, a build stalls in review.
What does it cost?
It depends on the sources, the permission model, and where it runs. We scope it with you during the AI readiness assessment, which runs about 3 weeks, and you have the full number before anything gets built.
Who owns the IP?
You do. You own all the IP and code AE Studio produces for you.