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.
Grant Free: $0/month with one project and monthly check-ins. Grant Pro: $49/month ($40/month billed yearly, 2 months free) with daily check-ins across five projects. Grant Studio: $149/month ($124/month billed yearly, 2 months free) with check-ins every six hours across fifteen projects.
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
AI-powered DevOps team with specialized agents for CI, costs, runtime, security and dependencies
Draft pull requests for supported dependency and compatibility fixes
Multi-channel access via Slack, dashboard, or MCP client
AWS cost tracking with forecasting and budget variance analysis
Security findings aggregation from GitHub and AWS Security Hub
World State monitoring for API changes and dependency updates
Decision tracking and follow-up management
Executive reporting and one-pagers on Studio and Enterprise
Agent security testing for prompt injection and AI risks
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
Complete AI DevOps team as a service, eliminating need to hire
Nothing merges or deploys without human approval and review
Specialized AI agents that each own specific operational domains
Evidence-based findings with citations from your actual sources
Works with your existing tools: GitHub, AWS, Slack, and your own AI providers
Since.dev