We build the environments where AI models do real work. Every step is checked against the right answer, so the model learns from what it gets wrong.
Pick a skill and find where models fail at it.
Turn it into tasks that each have a clear right answer.
Build the test so it cannot be gamed or memorized.
Make many versions. The early ones become training data.
Measure how often models succeed, then build the next test around what they miss.
Keeping AI safe and overseen. The first priority.
High-stakes work and stress-testing.
Bio, pharma, and research.
Real work inside real companies. Live today.
Built from real work, not made up. The skills carry over.
Coding, using tools, long tasks, and recovering from mistakes.
Built for the best models, on what they cannot do yet.