Agent harness infrastructure that gives AI agents memory for each user, connected accounts, action limits and an audit record.
Stage
Not given
Not given
Founded
Not given
Not given
Based in
US
CA
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.
Free: first 500 monthly-active end users per month, free forever. Paid: $0.30 per monthly-active end user above 500, billed monthly.
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
Timestamped memory ingestion with backdating capability
Per-user data isolation and privacy scoping
Ranked memory recall with dated evidence
Connected accounts integration per user
Long-running agent jobs with folder-level operations
Configurable token ceiling per API call
Enforced action limits on agent operations
Complete action audit trail with hash chaining
MCP server integration for Claude and other clients
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
Highest published BEAM benchmark score at 128K tokens: 85.1, compared to competing memory systems
98% fewer tokens required than raw tool output, making responses 4× cheaper
Works with 20+ agent frameworks including LangChain, LangGraph and LlamaIndex
First 500 monthly-active end users free forever
Per-person billing model scales with user growth, not API calls
Harny