The Enterprise Agent Build & Runtime for the work your business runs on
Stage
Not given
Not given
Founded
Not given
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Based in
US
Not given
Pricing model
usage-based
freemium
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.
Free plan with 50 workflow executions per month and visual editor. Enterprise plan with custom pricing includes governance, dedicated VPC, and comprehensive support.
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
Visual editor and AI copilot
No-code visual editor, exportable to Python
Code-first API built for total control
Real-time tracing of every LLM call, tool call, and memory read
RBAC and audit with immutable audit trails and Enterprise IAM
Human-in-the-loop approval gates and intervention during execution
Runtime hooks inject PII redaction and policy checks
Automated and human-guided training for continuous improvement
Multi-LLM testing for model swapping at runtime
GitHub integration
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
Agentic use case generator powered by billions of agent runs
Intelligently guided by 700k agent workflow patterns
Control Plane sits in execution path ensuring every agent interaction is observable, compliant, and reversible
Every production run turns into training data to sharpen accuracy and save money