The Trust Framework is how we decide whether to accept an engagement, how we run it once accepted, and how we refuse to deliver work that would fail by our own standards.
Published 2024 · Revised 2026 · Binding on every partner.
No fees, commissions, referrals, or revenue share from any technology provider, system integrator, or capital allocator. Our sole revenue is the advisory retainer paid by the client.
Every substantive claim we put to a client is annotated with its source: a document, a figure from a system of record, a named interview, a regulator's text. Claims without sources are removed.
The simplest system that does the job. Heuristics before classical ML before generative models before agents. Additional complexity is recommended only when the evidence of incremental value is plain.
A named, identifiable human owns every consequential decision made by or with an AI system. Ownership is not delegated to a vendor, a committee, or to the model itself.
Every system we recommend can be switched off within 30 days without structural damage to the business. Lock-in is a risk, not a strategy, and we cost it explicitly.
The Trust Framework predates most of the regulation that now applies to enterprise AI. It was written to produce compliant systems, and it does, across every jurisdiction our clients operate in.
In the briefing we walk the five principles against a real system of yours and tell you, on the record, where it passes and where it does not.