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02Engagements

A clear way to buy technically difficult AI work.

Each engagement has a defined decision or operating outcome. Scope follows the uncertainty, system boundaries, and evidence required, not a menu of generic AI services.

Engagements are scoped around defined outcomes.

Commercial model
Scoped engagements
Governance
Explicit stage gates
Delivery
Senior-led

Assure / Scoped evaluation

Independent AI assurance.

Commission a decision-focused assessment: technical due diligence and claim verification, technical challenge and defense, or adversarial interaction and behavior evaluation. Agree system boundaries, access, evidence requirements, evaluation artifacts, and a decision brief in the statement of work.

Scope assurance ↗

Delivery lifecycle

One operating method. Different levels of scope.

Technical and commercial decisions are tied to evidence at each stage.

  1. 01

    Define

    Business objective, constraints, data, economics, and success criteria.

  2. 02

    De-risk

    Test the assumptions most likely to determine success or failure.

  3. 03

    Engineer

    Build the system around evidence and explicit operating requirements.

  4. 04

    Validate

    Measure quality, failure modes, cost, latency, and reliability.

  5. 05

    Deploy

    Integrate the system into production infrastructure and workflows.

  6. 06

    Transfer or operate

    Document and hand over, or continue under a defined optimization scope.

Good engagement fit

What should be true before we start.

  • The business or engineering problem is material.
  • A technical decision-maker can participate.
  • Relevant data, systems, and constraints can be examined.
  • Success can be defined more precisely than “use AI.”
  • The organization can support security and procurement discovery.
  • There is a defined decision deadline or a credible path to operational adoption.