OUR METHODOLOGY
From evidence to accountable action.
AI can accelerate a workflow. Engineering judgement establishes whether its conclusions are sound. Our five-pillar framework keeps that distinction clear.
01 / Know
Define the asset and the question.
Bring together asset identity, design information, service conditions and operating history. Identify missing records and agree the scope before making an assessment.
02 / Assess
Make risk and uncertainty explicit.
Evaluate available evidence against the applicable technical basis. Separate measured facts, engineering assumptions and AI-generated suggestions. Escalate specialist assessments where required.
03 / Plan
Turn findings into a reviewable plan.
Prioritise work using agreed risk and criticality criteria. Define task owners, acceptance criteria, resources and the evidence needed to close each action.
04 / Execute
Keep the approved basis visible.
Work within facility procedures, permits and competent-person requirements. Record changes to scope and obtain the appropriate review before acting on revised recommendations.
05 / Assure
Verify the outcome and close the loop.
Check completion evidence against the agreed acceptance criteria. Record residual risks, unresolved questions and approval responsibilities for the next review.
HUMAN ACCOUNTABILITY
AI assists. Engineers decide.
AI outputs can be incomplete or incorrect. Verify calculations, units, references and applicability independently. No automated output should be treated as permission to operate or an assurance of safety.