Marketplace and runtime for headless, agent-first apps
Stage
Not given
Not given
Founded
Not given
Not given
Based in
US
Not given
Pricing model
Paid
Open source
Pricing
Usage-based pay-as-you-go pricing with hourly compute charges; committed contracts available for volume discounts. Hosted option with Anyscale-managed infrastructure or Bring Your Own Cloud deployment available.
Not given
Key features
Multimodal data curation at scale
Distributed model training with elastic scaling
Batch embedding generation at scale
Multi-cloud deployment and orchestration
Cluster-backed development environments
Workload-specific observability and debugging
Production-grade managed Ray clusters
Access control and governance
GPU budget controls and cost attribution
Post-training with SkyRL and veRL support
Install agent-first apps without graphical interface
Connect via MCP or REST protocols
Browse and install from marketplace
Run apps locally on your server or computer
Share app results between connected agents
Build custom apps using Python, JavaScript or containers
Test improvements before reusing apps
Keep apps private or publish to marketplace
Optional runner to track tasks without model API agent
Linux x86-64 and ARM64 support
What makes it different
Built by creators of Ray, the world's most widely adopted AI compute engine
Multi-cloud deployment without code changes
Feels local but runs distributed
Unified GPU pooling across clouds and regions
Data stays in your own environment
Add tools without changing agent harness
Multiple agents share results in same collection
Agents can create tools by automating repeated work
Rhyven