Safety & assurance for Physical AI

Bring safety into the engineering loop.

Ply operationalizes safety, cybersecurity and standards directly in the engineering workflow—connecting your robot to the requirements, controls, tests and evidence needed to ship.

Know what your change affects. Before you merge.

Change impact, traced
Warehouse robot
Perception
Worker interaction
Verification
Release
Perception threshold
Impact traced
− threshold = 0.72+ threshold = 0.64
Current evidenceSite 04 Review before deployment
02 — The problem
Physical AI

Evolves continuously.

Software · Models · Hardware · Environment

Engineering understanding

Manually reconstructed.

At points in time · Reviews · Audits · Documents · Snapshots

The robot changes continuously. Its assurance basis should too.

03 — Understand

Ply learns what it is reasoning about.

Ply extracts product and environment facts from engineering artifacts, determines what controls downstream assurance conclusions, and asks only when something important cannot be established.

Autonomous operationEstablished
Protective stopEstablished
Worker detectionEstablished
?Human access to operating areaUnknown
Ply found

1 decision needed to continue

Why this matters

Controls the worker-interaction safety path.

04 — Assurance graph

Standards become engineering work.

Ply turns applicable safety and cybersecurity requirements into connected engineering work—requirements, controls, tests and evidence grounded in the actual hardware, software and operating environment.

01Engineering state
02System
03Safety & cybersecurity
04Standards & requirements
05Tests & verification
06Evidence
07Release
One system. One Assurance Graph.Every relationship carries its basis.
05 — Ask

Ask Ply what the change means.

Ply does not answer from a generic chatbot. It reasons over the current engineering state, its Assurance Graph, and the evidence connected to it.

Engineer

“Can we increase maximum speed?”

Ply

“This changes two controlling assumptions and moves Site 04 outside the currently validated envelope.”

Need review3
Basis unchanged27
Verification to rerun1
See why →

Synthetic engineering example

06 — Change
One change · consequences everywhere

Understanding stays alive as the product changes.

ply propagates each engineering decision through the relationships, evidence and deployments that depend on it.

01End-effector replacedEngineering change
02Pinch-point hazard updatedConnected assurance state
03Force-limit assumption challengedReview required
04Force-limit test requiredTest to run
05Site 04 requires reviewSites 01–03 remain eligible
Change impact

A change shouldn’t restart your entire safety case.

Ply isolates the requirements, tests and evidence that need attention while preserving the work whose controlling assumptions still hold.

Synthetic engineering example · Change impactPR #184 · perception threshold 0.72 → 0.64
Needs attention
Worker detectionReview
Low-light validation suiteRerun
Site 04Hold
Basis preserved
Emergency stopBasis unchanged
Braking controllerBasis unchanged
Sites 01–03Evidence still applies
3 things to revisit. 27 whose basis hasn’t changed.

Every decision is inspectable.
Every conclusion has a basis.

07 — Trustworthy Physical AI
Understanding is the substrate

Engineering understanding is the engine.

01Continuous assurance.

What still holds?

02Traceability and verification.

What must we prove?

03Release readiness.

Can we deploy?

From engineering state to deployment decisionOne connected basis for trust.
08 — Ply
Engineering assurance for Physical AI

Safety by design.Compliance as a byproduct.

Operationalize safety, cybersecurity and standards directly in the engineering loop—and keep requirements, tests and evidence current as the system evolves.

Build with ply