IO42 is the infrastructure that lets AI agents safely operate heterogeneous robot fleets in production — with the orchestration, policy, and observability primitives that physical autonomy demands.
Every team building agent-driven robotics rebuilds the same primitives — fleet orchestration, safety policy, telemetry, human override — on top of vendor SDKs that were never designed for autonomous, multi-agent operation.
The result is brittle stacks, slow iteration, and no path to scale beyond a single pilot. Vendor SDKs are single-robot. ROS 2 is a middleware, not a control plane. There is no Kubernetes for robot fleets.
Every vendor ships its own SDK, its own command model, its own telemetry format. Mixed-fleet operation is glue code all the way down.
Agent autonomy in the physical world needs declarative policy, hard rails, and audit trails. Today these are reimplemented per deployment.
When an agent does something unexpected, there is no observability primitive that lets you replay the decision, much less debug it.
IO42 sits in the middle. Agents call a single API. Robots speak through unified drivers. Policy, observability, and human supervision are first-class primitives — not afterthoughts bolted on per deployment.
A unified API across robot vendors and form factors. Schedule, dispatch, and coordinate mixed fleets without writing per-vendor glue code.
Declarative policy for what agents can do, where, and under which conditions. Hard safety rails, soft operational guardrails, full audit trails.
Every command, every state transition, every agent decision — captured, queryable, replayable. Debug autonomous behavior like distributed systems.
Operators supervise fleets, not individual robots. Intervene, override, or hand back control with a single primitive — built for the autonomy gradient.
VLA models, long-horizon planners, and tool-using LLMs have crossed the threshold where physical autonomy is no longer a research problem.
AMRs, humanoids, and manipulators are all sliding down the cost curve simultaneously. Fleet deployments at meaningful scale are now economically viable.
Every operator is rebuilding the same orchestration, policy, and observability primitives. None of it compounds. None of it is sharable. None of it is finished.
Every supported robot platform and agent framework deepens the moat. Network effects play out on both sides of the control plane.
Policy and governance for physical autonomy is the hardest part of the stack — and the part vendors cannot ship. We make it portable.
Every deployment makes the platform smarter about real-world failure modes. Telemetry compounds into better defaults, better policy, better autonomy.
06 / End of brief
Build on IO42. Currently onboarding design partners.