Business users build simple agents with no code; developers use pro-code tools and AI-assisted coding for advanced ones. Extend safely with sandboxed custom tools, so your team focuses on differentiation, not infrastructure plumbing.
Prove agents before you ship them with integrated, AI-assisted evaluations that benchmark model quality and catch inconsistent or biased outputs. Built-in resilience and automatic failure recovery keep mission-critical agents reliable under real-world conditions.
Promote agents through GitOps, versioned and staged from test to production using the tooling you already run. Scale cost with processing, not agent count, and deploy self-hosted or fully managed on any cloud, with any model.
See and supervise every agent action with built-in human-in-the-loop approvals and a sovereign control plane for governance, RBAC, and audit. Track and optimize LLM token spend by agent, model, and task to control cost.
Keep improving agents through log annotations and self-improvement fed by live events, closing the gap most teams hit: no repeatable way to observe, evaluate, and improve agents once they’re live.







