Engineering-grade AI advisory for organisations where models touch regulated outcomes, safety-critical systems, or public trust.
MRBF engages on AI where the question is not 'can a model be built' but 'should it be deployed, how is it governed, and who is accountable when it fails'. We work alongside in-house data, engineering, and risk teams rather than replacing them.
Model inventories, risk classification, human-in-the-loop design, and the documentation regimes that survive audit and regulator scrutiny.
From pilot to production — data pipelines, MLOps governance, accountability structures, and the operating model that owns models in the field.
Support to government on AI procurement standards, evaluation frameworks, and sectoral guidance where general-purpose policy meets specific industry risk.
Independent review of AI ventures and AI components — model defensibility, data rights, infrastructure costs, and credible path to regulatory acceptance.
Where AI enters control loops, safety cases, and certification environments — review of assurance evidence, failure modes, and operator interface design.
Executive and board-level programs that build the technical literacy required to govern AI, not just authorise its purchase.
Illustrative scenarios drawn from the kind of problems MRBF is equipped to engage on in this domain. Anonymised by design — specific principals and outcomes are confirmed in scoping and governed by confidentiality.
Designed evaluation criteria, evidence requirements, and post-award assurance obligations for AI-enabled tooling, aligned with emerging national policy.
Illustrative · scoped under confidentiality
Independent review of an ML-based predictive maintenance system before fleet-wide rollout, covering data integrity, drift management, and operator override design.
Illustrative · scoped under confidentiality
Engineering-led diligence on data moats, infrastructure economics, and regulatory exposure for a growth-stage AI company entering regulated markets.
Illustrative · scoped under confidentiality
Engagements begin with a scoping conversation. We confirm the problem, the senior practitioners or specialists who would deliver, and whether MRBF is the right counterpart before any work starts.