The enterprise question isn’t capture. It’s control.
On a Tuesday, the first enterprise question is usually not “can you capture AI code?” It’s “who can see the records, how long do they live, and what happens when a policy blocks a change?”
That’s the part LineageLens is built for. Base gives you local capture. Lite gives a shared team record. Plus and Max move the data into a backend where auth, permissions, retention, and policy live next to the provenance records instead of around them.
The useful thing here is not another dashboard. It’s a self-hosted record of prompt, model, tool, file, and outcome that engineering, security, and platform teams can actually govern on their own infrastructure.
I keep seeing AI governance tools start with “visibility,” then discover that the real enterprise questions are identity, retention, and review. If the record cannot be scoped, retained, and exported on your side, it is not really governable.
What would your team need first: SSO, retention, or a review policy that developers will actually use?
Replies
The point about governance semantics needing to be embedded in the record rather than layered around it hits really close to what we've seen working with enterprise AI deployments. When policy and provenance are decoupled, audit trails start depending on everything staying perfectly aligned — and they rarely do in practice.
On the SSO vs retention question: in highly regulated environments (banking, healthcare), retention tends to surface faster than people expect because those records immediately become potential compliance artifacts, not just logs. SSO is the trust entry point, but retention is where legal and security teams actually get nervous.