An OpenEnv benchmark testing the ability of AI agents to act as Site Reliability Engineers (SREs) by diagnosing and filtering raw production failure logs.

Deterministic evaluation environment for AI code reviewers covering bugs, security (OWASP), and architecture via FastAPI + OpenEnv.

AI-powered system for low-exposure route optimization using AQI, simulation, and intelligent decision-making

AI research environment that simulates the end-to-end scientific discovery process, enabling agents to analyze papers, generate hypotheses, design experiments, and validate results collaboratively

📧 Intelligent Agentic Workflow for Autonomous Enterprise Email Triage. Built with OpenEnv, featuring Chain-of-Thought reasoning and Self-Correcting agent logic for high-stakes corporate routing.

Gymnasium RL environment for AI-powered customer support triage — classify, prioritize, assign, and respond to emails under SLA pressure. Built for the Meta PyTorch Hackathon under the OpenEnv spec.

An OpenEnv-compliant reinforcement learning environment designed to train and evaluate AI agents on real-world SQL debugging, performance tuning, and schema design.

High-fidelity Reinforcement Learning environment for smart grids. Features a custom DC Power Flow physics solver and real-world AT&C telemetry to train AI in power distribution and fault isolation.

Adaptive Clinical Trial Design RL Environment

A reinforcement learning agent that learns to intelligently shape electricity demand, reducing peak loads and optimizing energy consumption in real-time.

RunbookOps: Deterministic OpenEnv environment for SaaS incident triage, runbook-driven resolution, and agent evaluation.

OpenEnv Hackathon SF

CNN based PPO agent and LLM based GRPO agent to play SMB on openenv wrapper using Leirbag-gabrieL's gym-super-mario-bros fork

PyTorch Training Optimization RL Environment

Chess OpenEnv Multi-Agent System

Agentic Reinforcement Learning Loop to make Scientific Discoveries on Mars

A production-grade OpenEnv environment for benchmarking RL agents on real-world data cleaning and schema engineering tasks.

Production MLOps operations environment for RL agent training. 3 tasks: data quality triage, deployment decisions, incident cascade. Dense rewards, causal state transitions, deterministic graders. Built for OpenEnv Hackathon (Meta × HuggingFace × Scaler).

🐛 Real-world GitHub issue triage environment for AI agent training — built on the OpenEnv spec with 3 difficulty-graded tasks, shaped rewards, and FastAPI server deployable to HuggingFace Spaces.

Adaptive RL Reliability is an OpenEnv-compatible reinforcement learning environment for live-system autoscaling. It trains agents to make production capacity control decisions (scale down/hold/up) while protecting SLOs for latency, error rates, and CPU usage.