Governance infrastructure for Physical AI.
ply connects engineering changes to safety, regulations, evidence, runtime validation, and release decisions, so robotics teams can ship AI-enabled systems with confidence.
Physical AI changed. Engineering workflows didn't.
Robots now evolve through software updates, AI models, new capabilities, and changing operating environments. Safety, cybersecurity, release readiness, and evidence still live across disconnected tools and documents.
Continuous product change
AI-enabled systems keep moving after launch.
Emerging regulation
Safety, AI, and cybersecurity obligations are becoming lifecycle questions.
Fragmented evidence
Records drift away from the engineering decisions that created them.
From engineering change to release decision.
Product facts
Capture what the robot is and where it operates.
Governance reasoning
Connect facts to claims, obligations, and risks.
Safety impact
Identify what changed in the safety case.
Evidence tasks
Assign missing proof to the right owners.
Release gate
Review what blocks or clears deployment.
Runtime validation
Map deployed behavior back to assumptions.
One control plane for Physical AI governance.
Product profile
System facts, intended use, autonomy, and environment.
Obligation map
Requirements tied to product decisions.
Safety impact review
Change assessment before release.
Evidence tasks
Owner-specific proof with status.
Release gates
Clear, blocked, or needs review.
Runtime validation
Deployed behavior checked against assumptions.
Not another document repository.
Engineering-first
Starts from the robot and its intended use.
Reasoning layer
Connects facts, claims, evidence, and release impact.
Runtime-aware
Maps deployed events back to assumptions and obligations.
Human-in-the-loop
Engineers review, approve, and override with traceability.
Ship faster. Stay governed as your robot evolves.
Bring safety, evidence, runtime validation, and release decisions into one engineering workflow.
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