EdotEnv GmbH develops RL environments and benchmarks for AI research tasks. The company focuses on quantitative research, post-training, and evaluating agents in increasingly difficult environments.
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RL environments built from financial market data for multi-step research tasks, hypothesis formation, experiment design, verification, and iterative post-training of agents.
Benchmarking for Autonomous Research
Benchmarks measuring agent capabilities in quantitative research and nonstationary long-horizon settings across hundreds of decisions.
Evaluation and Post-Training Environments for AI Research
Evaluation and post-training environments for frontier AI labs and academic groups, with research harnesses and benchmarking setups.
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