Where our work matters most.
We concentrate on sectors where AI carries direct consequence — financial, clinical, civic, or reputational. The harder the trust requirement, the better the fit.
01
Finance
Model risk, supervisory expectation, and the burden of proof
Banks, insurers, and asset managers are deploying AI into decisions that regulators already scrutinise. The constraint is rarely capability — it is the ability to evidence how a decision was reached, by which model version, on which data, under whose approval.
Read the sector view02
Healthcare
Clinical consequence, patient trust, and non-negotiable safety
Providers, payers, and life-sciences organisations operate where an unexplained output is a patient-safety event. Governance here is not documentation — it is the clinical safety case, held continuously rather than at approval.
Read the sector view03
Public Sector
Procuring, deploying, and governing AI in the public interest
Agencies and regulators carry a dual burden: using AI well and holding others to account for it. Both demand transparency that survives freedom-of-information requests, parliamentary scrutiny, and public challenge.
Read the sector view04
Media
Provenance, attribution, and synthetic content at scale
Publishers and platforms face a credibility problem before they face a technology problem. Authorship, attribution, and provenance are now the product — the ability to say what a thing is, who made it, and how.
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Enterprise SaaS
Shipping AI features and the trust posture that requires
Software companies now sell into buyers whose security reviews ask harder questions than their own boards do. Trust posture has become a sales dependency, and it is fastest to build into the product rather than around it.
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