Research-backed education and tools for securing autonomous AI agents
Stage
Not given
Startup
Founded
Not given
2025
Based in
US
US
Pricing model
Paid
Paid
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
AgentGuard360 dashboard and Agent Proxy Tool Interface
Supply chain protection blocking 11,000+ known malicious pip and npm packages
14-phase device hardening scans with predictive risk analytics
Machine-learning-aided runtime scanning of agent content
Jailbreak detection and prompt injection prevention
Privacy-first architecture keeps data on device by default
500+ model pricing with budget tracking
Protection SDK with single function call content scanning
Learning Center with guides, how-tos, and CVE analysis
Original research on agentic AI and LLM cost optimization
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
No PhD in security required to protect AI agents
Free resources and research with optional paid tools
AI Security Guard