Muhammad Usman

I ve been thinking about this over the past few weeks, especially as larger tech corporations that weren t originally built around AI (Oracle, Meta, ClickUp, etc.) have started mass layoffs in favour of more efficient AI-driven solutions.

From that, it seems like AI companies must be doing extremely well and are actively trying to protect their positions. This also suggests that to strengthen their position (besides AI itself), they still need human capital to help them grow.

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.