Build and ship RL environments on a single, collaborative platform
Open source infrastructure to develop, version, test and train reinforcement learning environments at scale. Enterprise-grade RL infrastructure that leading AI labs spend billions on, minus the billion-dollar price tag.
> RLHUB v2.1.3 - Distributed Training Framework > Environment: gym.HumanoidStandup-v2 (commit: a83fc2d) > Training architecture: Distributed PPO with custom replay buffer > Hardware allocation: - 4 × nodes (node1.cluster → node4.cluster) - 16 × NVIDIA A100 GPUs (4 per node) - Memory: 640GB (160GB per node) > Initializing multi-node coordination layer > [node1] ✓ Connected - Primary orchestration > [node2] ✓ Connected - Training worker > [node3] ✓ Connected - Training worker > [node4] ✓ Connected - Training worker + evaluation > Launching distributed workload with 128 parallel environments > Environment config: ./configs/humanoid_standup.yaml > Training policy: PPO (clip=0.2, epochs=10, lr=2.5e-4) > ▓▓▓▓▓▓▓▓░░░░░░░░░ 41% complete > Current reward mean: 387.4 ± 42.6 (↑11.2% from last checkpoint) > Policy loss: 0.0423 | Value loss: 0.0217 | KL div: 0.0183 > Training throughput: 13,520 steps/sec (33.8M steps total) > GPU utilization: node1=94%, node2=97%, node3=96%, node4=94% > Live visualization: https://rlhub.dev/train/f82a3
Collaborate on RL like never before
Real-Time Collaboration
Build better RL environments together with seamless teamwork
Multi-User Editing
Real-time environment development
Environment Sharing
Fork and improve together
Shared Metrics
Analyze results together
Collaborative Environment Stats
100+ Developers Already Using RLHUB
Reinforcement learning unlocks autonomous agents, but infrastructure challenges hold teams back
Reproducibility Crisis
Without proper environment versioning, researchers waste countless hours trying to reproduce results, with subtle differences causing unexplainable performance variations.
Prohibitive Infrastructure Costs
Leading AI labs invest billions in RL infrastructure. Most teams lack these resources, yet need enterprise-grade capabilities to compete.
Team Collaboration Barriers
Researchers and engineers work in silos with incompatible tools, hindering progress on complex RL challenges that require cross-functional expertise.
Everything you need to build and ship RL environments
Version control, distributed training, and performance tracking in a single platform
Environment Version Control
Git-like versioning system for RL environments. Fork, branch, merge, and collaborate on environments with complete history tracking and reproducibility.
Distributed Training
Scale training across your GPU clusters with automatic workload distribution, checkpoint management, and fault tolerance for massively parallel training.
Performance Tracking
Comprehensive metrics tracking for agents and environments. Compare experiment results, visualize learning curves, and identify optimal hyperparameters.
Environment Marketplace
Discover, share and collaborate on RL environments with the community. Fork popular environments or contribute improvements back to the ecosystem.
Choose the plan that fits your needs
Powerful RL environment infrastructure for teams of all sizes
Community
For hobbyists and small teams ready to join our open-source community
Everything you need to spin up your first RL environment:
- Unlimited public environments
- Unlimited members within a single organization
- Basic environment version control
- Access to platform UI, CLI, and API
- 500 training minutes/month
- Community support via Discord and GitHub
Premium
For enterprises ready to achieve world-class security, scalability, and developer experience
Includes everything in Community, plus:
- Ticket-based global support with SLA
- Multi-organization access controls
- 50,000 training minutes/month
- Audit logging to monitor user operations
- Resource quotas per organization and user
- High availability deployment options
- Custom branding options
Compare plans and features
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Join 100+ developers at Stanford and YC startups building agents with our platform. Get enterprise-grade RL infrastructure without the billion-dollar budget.