Autonomous RL environments
Environments that build themselves.
Attoloop finds what models can't do yet, builds the data, writes the environment and tests it hard, so it's ready before you train on it.
Three foundries. One loop.
- ResearchEnvFoundryFinds the skills models still fail at.
- DataDataFoundryTurns raw sources into clean, licensed, calibrated tasks.
- EnvironmentEnvFactoryWrites the environment, then tries to break it.
Attacked before it ships.
A variety of attackers
Different models and strategies probe every verifier, each on its own.
Solving isn't cheating
An attack counts only if it scores higher than the reference solution without doing the work.
Sealed while it works
No network during the task, and eval answers stay out of reach.
Hand‑written by no one.
Expert networks
- Each environment waits on a specialist
- Graded by rubrics that people score
- Output grows with headcount
Attoloop
- Agents build around the clock
- Graded by deterministic verifiers
- Output grows with compute