See every AI interaction across your organization. Start with the free desktop agent, scale with the platform.
We're coming out of stealth and joining Y Combinator's Winter 2026 batch. Here's why we're building the visibility layer the enterprise has been waiting for.
Enterprise AI adoption accelerated because it was useful. What didn't evolve at the same pace was visibility. Here's why that's the biggest risk to scaling AI safely.
As AI systems influence decisions, automate workflows, and shape outcomes, responsibility is quietly diffusing. When something goes wrong, the organization often discovers that no single team fully owns the system involved.
Employee AI observability does not fail at the prototype stage. It fails when AI becomes a daily habit. Here's why tracking workforce AI usage requires a fundamentally different approach.
Nearly every enterprise that reaches meaningful AI adoption encounters the same moment of clarity: how do we see what's happening without slowing everything down? That's when the build-versus-buy discussion begins.
A practical, thirty-day path from uncertain AI usage to defensible, governed adoption - designed for organizations that need to move now, not eventually.
AI agents do not merely respond. They act. They browse, call APIs, write files, trigger workflows, and make decisions that have real operational consequences. This fundamentally changes the security model.
Most enterprises already have an AI policy. It sits alongside information-security guidelines and acceptable-use standards. On paper, it looks like progress. In practice, it rarely governs anything.
Shadow AI is not simply the next iteration of shadow IT. It is categorically more dangerous because AI systems move data, interpret intent, and generate outcomes in ways traditional tools never did.