Product features

Built for accountable physical AI

Agent bridges solve access. Groundpasse solves deployability โ€” verified execution, enforced safety, and complete audit trails so teams can ship agent-driven robotics with confidence.

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Behavior contracts

Reusable, versioned behaviors โ€” patrol, dock, inspect, timed drives โ€” with safety rules and preconditions built in. Contracts are hashed, registered, and referenced on every intent so you always know exactly which recipe ran.

Not one-off prompts. Not ad-hoc scripts at runtime. Behaviors are reviewed, tested, and promoted like software releases.

  • YAML-defined contracts with schema validation
  • Preconditions: battery, localization, clearance gates
  • Invariants enforced continuously during execution
  • Version pinning via contract reference on each intent
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Intent interface

Any AI agent, operator tool, or integration submits structured intents โ€” goals and parameters, not motor commands. Groundpasse accepts the request, validates it, schedules execution, and exposes status over HTTP and JSON-RPC.

Agents never publish directly to cmd_vel or joint topics. They describe outcomes; the runtime owns motion.

  • REST intent API with polling and cancellation
  • Python and TypeScript client adapters
  • Deadline and priority on submitted jobs
  • Shadow mode for parallel sim comparison
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Safety governor

A dedicated safety layer sits on every motion command path. Speed caps, proximity stops, zone violations โ€” clamped or blocked before actuators respond. Agents and contracts cannot bypass this layer; only physical e-stop or operator override can.

That is the ground pass: explicit safety approval before anything touches ground.

  • Per-command velocity and acceleration limits
  • Intervention logging inside every episode
  • ROS 2 bridge applies governor on live hardware
  • Independent of agent reasoning โ€” deterministic enforcement
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Episode records

Every run produces a complete audit trail: what was requested, which contract ran, every precondition result, governor intervention, sensor snapshot, and final outcome. Episodes are the diary of physical AI โ€” replayable, diffable, certifiable.

  • Web viewer for timeline and event inspection
  • Diff two episodes to spot behavioral regression
  • Certification reports for compliance workflows
  • Retention policies for long-running deployments
Mixed robot fleet

Fleet management

Multiple robots โ€” quadrupeds, humanoids, AMRs โ€” one control surface. Register capabilities, assign intents to the right base, and track outcomes across the fleet without separate silos per robot type.

  • Robot registry with capability tags
  • Intent routing by skill and availability
  • Unified episode store per deployment
  • World memory for persistent site context
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Behavior benchmarks

Standard scenarios score how reliably behaviors perform โ€” in simulation or on real hardware. Run benchmarks in CI, compare across contract versions, and catch regressions before they reach the floor.

  • Curated scenario library (patrol, dock, inspect, โ€ฆ)
  • Sim and real execution paths
  • Automatable via make bench in development
  • Marketplace catalog for shared contract templates

See how features connect in the execution flow.

How it works Request a demo