The all-in-one agentic AI solution for your organization
Stage
Not given
Startup
Founded
Not given
2024
Based in
US
Not given
Pricing model
Paid
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.
Starter (free), Professional ($29/seat/month), Enterprise (contact for pricing)
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
Centralized context repository for unifying work signals across tools
MCP protocol integration with AI assistants and tools
First-class integrations with GitHub, Vercel, Supabase, Railway, Gmail, Notion, Calendly, Codex, Claude Code, and Slack
Per-agent scoped access with full audit trail
Custom vector embeddings for agent memory
Instant agent shutdown from anywhere globally
QUAERO enterprise AI agent governance system
Two-way sync with tools for agent actions and work flows
Support for custom MCP servers and internal tools
Real-time organizational context for agent reasoning
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
AI-first design with structured, queryable context rather than static documentation
Consistent policy and audit rules across all integrations
MCP-native integrations with no bespoke connectors to maintain
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