Define the limits
Intended use, operating conditions, failure scenarios and human intervention.
Physical AI safety and platform readiness
Connect AI behaviour, operating limits and safety evidence before a physical trial or wider deployment.
When it helps
AI can influence movement, equipment, access or another outcome in the physical world.
Bring what you have
Your requirements, the current design and the questions you need to resolve.
The work
Intended use, operating conditions, failure scenarios and human intervention.
NVIDIA and Hailo options, integration constraints and measurable performance.
Scenario tests, traceable findings and preparation for specialist safety review.
Establish what the system is expected to sense and do, where it will operate and how people interact with it. Identify situations it should recognise as outside its permitted operation and the response expected when inputs, communications or compute resources fail.
The result is a clear system boundary and an agreed set of questions for engineering and safety review.
Connect the important failure scenarios to evaluation requirements. Define what can be tested in simulation, on the bench or in a controlled environment, and where evidence needs to come from the intended site.
We help organise assumptions, test results, limitations and unresolved issues so that a decision-maker or specialist assessor can follow the reasoning. Tests need to support specific claims about the system; a strong average score alone does not establish a safe operating range.
Assess NVIDIA and Hailo options against the actual workload and integration constraints. Consider model support, sensor inputs, host processing, response time, power, heat, update arrangements and behaviour under degraded conditions.
For Hailo, this can include model conversion and evaluation around the relevant software toolchain and host integration. For NVIDIA, it can include edge architecture and the applicability of safety-oriented platforms and tooling to the proposed use.
NVIDIA Halos brings together physical AI safety technologies and an inspection ecosystem. For teams considering it, we can help establish what is relevant to the project, map the available design evidence and prepare the questions needed for programme and assessment discussions. NVIDIA Halos.
Our role is advisory and engineering support. Formal Halos inspection and any subsequent system certification follow the applicable provider’s process.
Physical AI readiness review
A focused review of the intended operation, system boundary, important failure scenarios and current evidence. Output: a decision brief and prioritised workplan.
NVIDIA or Hailo feasibility study
Assess the fit of a proposed platform and test the main deployment uncertainties. Output: configuration-specific findings, integration requirements and a recommendation for the next stage.
Safety evidence preparation
Organise requirements, assumptions, tests and open issues for an internal release review or an external specialist assessment. Output: a traceable evidence structure and a clear view of what remains to be demonstrated.
We agree the contribution of the product owner, engineering team, safety specialists and assessment bodies at the start. A platform’s safety features support the system design; the finished application still needs evidence for its own use and environment.
The intended action, operating environment and stage of development are enough to start a useful conversation.
NVIDIA Halos concerns physical AI safety. Hailo develops edge AI processors and platforms. We help with the relevant readiness, integration and evaluation questions; they are distinct organisations and offerings.
We prepare evidence and support readiness. Formal safety assessment and certification follow the applicable specialist route.
A useful place to start
Tell us what you are building, adopting or trying to understand.