New We Release AutoLab: Benchmarking Frontier Models on Autonomous Research The infrastructure where
The infrastructure where
AI learns to do real work.
Agents need more than static data. They need environments, evaluation, and expert guidance.
Diagnosis · Evaluation · Expert Data · RL Environments
Leading AI labs use our open-source infrastructure to make AI systems work in the real world.
and more Benchmarks & Infrastructure
AI Can't Game
Product
Bake AI Infrastructures
From failure diagnosis to real-world training
Domain Coverage
Critical Decisions
- Finance & Risk-Sensitive Decision Making
- Safety, Alignment, Red-Teaming
Verifiable Tasks
- Coding & Software Engineering Agents
- STEM & Multimodal Reasoning
- Auto Research
Human Judgment
- Writing, Judgment, EQ
- Aesthetic & Art
BakeLab Research
The science behind reliable AI.
AutoLab: Can Models Begin to Participate in the Loops That Drive Scientific and Engineering Progress?
Auto Research Benchmark Blog Post
Visual Aesthetic Benchmark: Can Frontier Models Judge Beauty?
Visual Aesthetics & Evaluation Blog Post
PersonaMem-v2: Towards Personalized Intelligence via Learning Implicit User Personas and Agentic Memory
Personalization & Agentic Memory Preprint
Building a Foundational Guardrail for General Agentic Systems via Synthetic Data
Agent Safety ICLR 2026
CoDA: Agentic Systems for Collaborative Data Visualization
Agentic System ICLR 2026