Governing agentic AI like the distributed system it actually is.
Agent fleets fail the same way distributed systems did before we learned to govern them: six months in, nobody can say how many agents are running, what each one does, which tools they share, or whether any of it still matches the design. The models are fine. What's missing is the scaffolding that keeps a fleet of autonomous components legible, validated, and governable — a registry, typed contracts, and a way to see (and verify) the whole estate.
Fox River AI builds that scaffolding.
An Erwin-style visual modeler for agentic AI platforms. Lay out the whole system — orchestrator, tasks, agents, MCP tools, jobs, model routers, and the datastores they touch — as one collapsible model; validate it live; export a version-controlled registry that becomes the source of truth for building and governing the fleet.
▶ Try it live — in your browser, no install.
⚙️ agent-atlas
The open engine the studio is built on: the manifest schema (the single source of truth for every agent and tool) and the deterministic validators and governance hooks. Apache-2.0.
Model the platform → export the registry → generate the contract (CLAUDE.md)
and the enforcement hooks a coding agent builds against → and (next)
reverse-engineer the running system to prove it still matches the model. Design,
build, verify — for agent fleets.