We are building thetrust and verificationlayer for AI

Our founders built models for Siri and Vision Pro across multiple teams, and kept rebuilding the same infrastructure to evaluate how those models performed. Because Apple is so privacy-oriented, there was no shared system for evaluation, observability, or governance, so every team solved the same problem from scratch.

Some of those models powered core Siri, like the natural language systems already shipping to hundreds of millions of people. Others were for projects not yet released, like Vision Pro. From both vantage points we saw the same question: how do you know a model will work well for all kinds of people and situations? At Apple we could test that Siri worked when someone called 911, but never anticipate every real-world edge case, such as a baby crying, road noise, or a HomePod answering from another room.

2021We founded the company to catch those edge cases before shipping, instead of waiting for users to find the gaps. We named it Openlayer to capture the idea of opening up the layers of an AI system: the layer of your workflow built to understand your AI, open and transparent by design. We started as Unbox, for unboxing the black box of a model, and changed the name to avoid conflicts.

Over time we grew from pre-deployment testing into production monitoring, so engineers could test thoroughly before shipping, find gaps quickly in production, fix them, and redeploy with far faster iteration velocity. In the last couple of years, as generative and agentic AI became easier to build and more powerful, we added a third focus: governance and AUTOMATED COMPLIANCE.