Quality for AI that acts on the physical world
Physical AI puts autonomous agents into the real world — where a defect is no longer a wrong pixel but wrong motion. TestLauncher brings agentic testing, institutional knowledge, and continuous compliance to embodied systems, so evidence — not luck — is what stands between your agents and the physical world.
What makes quality hard in physical ai
Perception and action under uncertainty
Real-world inputs are a long tail, not a happy path. Coverage has to reach the rare, adversarial, and out-of-distribution cases that scripted tests never imagine.
Non-determinism at the edge
Every model update can change behavior. You need reproducible evaluation and automatic regression detection across versions — not a one-time acceptance test.
Evidence for a moving regulatory frontier
Safety cases and audit trails are expected before the standards fully settle. The evidence has to be a byproduct of how you build, not a scramble before review.
Knowledge that outlives the model
When a system fails, the reason has to be captured so the next model does not relearn it. Institutional memory is the difference between compounding and repeating.
One intelligence layer for physical ai
The same owned QA Brain — testing, knowledge, and compliance — focused on the risks this sector can’t afford to get wrong.
bugAgent
Autonomous exploration of edge cases and scriptless regression that adapts across model versions — surfacing failures before the field does.
ARC
Continuous compliance monitoring and evidence generation, so a defensible safety case accumulates as you work.
qualThread
The digital thread linking requirements to tests to observed field behavior — traceability that survives model turnover.
manualTesting
Expert human review where physical consequences demand judgment automation cannot yet provide.
Designed to support the regimes you work toward
TestLauncher is designed to support programs working toward the standards below and generates the traceability and evidence they call for. Naming a standard here is not a claim of certification — it describes the regimes our customers operate in.
- ISO/IEC 42001
AI management systems — governance for how AI is built and operated.
- ISO/IEC TR 5469
Functional safety and AI systems — how AI fits into safety-related functions.
- IEC 61508
Functional safety of electrical/electronic safety-related systems (the base regime).
- UL 4600
A safety-case standard for autonomous products without a human driver/operator.
Bring the QA Brain to physical ai.
Powered by bugAgent, ARC, qualThread, manualTesting. Tell us where quality can’t fail and we’ll show you what an owned intelligence layer looks like for your programs.