The advisory pillar
AI consulting that ends in decisions, not decks
We install the operating model that lets an enterprise run AI safely and repeatedly: a scored baseline, decision rights, a sequenced roadmap, and named owners against every gap.
- Typical entry
- AI Readiness Diagnostic, four to six weeks
- Method
- The NATIVE framework, published in full
- Commercials
- Fixed fee, fixed duration, named deliverables
The situation
Most AI programmes stall for organisational reasons, not technical ones
The models work. The pilots demo well. What is missing is the surrounding machinery: a baseline anyone agrees on, a workflow that changed, an owner who can be held to a number, and a rule that says who may override the system. Without those, every pilot becomes a permanent pilot, and the organisation learns that AI is something that gets demonstrated rather than something that runs.
Our advisory work fixes the machinery first. It is deliberately unglamorous, and it is the reason the build work that follows survives contact with an audit.
You are probably seeing
- Several pilots running, none of them in production with a named operational owner.
- A board asking for an AI position paper with a number attached to it.
- Staff using consumer AI tools that nobody has inventoried.
- Vendor decisions being made before the workflow question has been answered.
Engagements
AI strategy and operating model
Where the baseline, the sequence, and the decision rights get written down.
3 to 4 weeks
AI Readiness Diagnostic
A scored assessment across leadership commitment, data usability, workflow clarity, and governance, with a named owner assigned to the weakest pillar
Pre-Proof
4 to 6 weeks
AI Strategy and Roadmap
A sequenced twelve-month plan built from a triaged use-case shortlist, each item carrying a metric, an owner, and a validation method
Pre-Proof
2 weeks
Use Case Portfolio Design
Reduce a long list to a defensible shortlist using three gates: strategic consequence, measurability, feasibility
Pre-Proof
4 to 6 weeks
AI Operating Model Design
Decision rights, governance cadence, funding model, and the choice between a central centre of excellence, federated pods, or both
Platform
Monthly, six-month minimum
Fractional Chief AI Officer
Senior AI leadership on a defined monthly commitment, owning the loop rather than advising on it
Platform
Half day or full day
Board and Executive Briefings
Half-day and full-day sessions for boards and leadership teams, built on the NATIVE framework and the RAO prompt standard
Pre-Proof
Engagements
Governance and risk
The controls that let a regulated organisation deploy without waiting for a policy that never arrives.
4 to 8 weeks
AI Governance Framework
A standing governance discipline with approval, override, and escalation named per workflow, not per company
Product
3 to 5 weeks
AI Policy and Acceptable Use
An enforceable enterprise AI use policy, plus the shadow-AI inventory that tells you what is already running
Pre-Proof
4 to 8 weeks
Model Risk and Assurance
Evaluation harnesses, quality bars, drift monitoring, and audit-ready documentation for regulated workflows
Product
2 to 3 weeks
AI Vendor Due Diligence
Contract, portability, and exit-cost review, with specific attention to fine-tuning data portability and lock-in
Platform
The method
NATIVE, six stages
Every advisory engagement runs through the same loop. It is published in full and free to use, whether or not you hire us.
- NNoticeWhat the market is already telling you
- AAssessAre you ready, really?
- TTargetChoosing the battlefield
- IIntegrateRewriting workflows and decision rights
- VValidateProve it before you scale it
- EExpandWhen the pilot becomes reality
The other pillar
Advice that has to survive being built
We are also an AI software development firm. The roadmap is written by people who will have to ship against it.
What we decline
- Programmes with no named executive owner.
- Benchmarking exercises intended to justify a decision already made.
- Pilots with no baseline measurement and no stop condition.
- Any claim about a partner tier or certification we do not hold.
FAQ
Questions about AI consulting
- What does an AI consulting engagement actually produce?
- A written baseline, a scored readiness picture with named owners, a sequenced roadmap with costs, and the decision rights that say who may approve, override, and escalate an AI-assisted decision. Documents you can act on, not a deck.
- How is this different from a strategy firm's AI practice?
- We build the software as well. The advisory work is written by the people who will be accountable when the system runs in production, which changes what gets recommended.
- How long before we see something real?
- The Diagnostic runs four to six weeks and ends in a decision. A Prototype Sprint runs two to three weeks. We do not sell twelve-month transformation programmes with the first deliverable in month five.
- Do you require a diagnostic before a build?
- Not if you already have a written baseline, a named owner, and a metric you will be held to. If those are missing, we say so instead of billing for a build that cannot be judged.
Next step
Start with a baseline, not a proposal
Take the NATIVE Audit in fifteen minutes, or book a scoping call and bring the pilots you already have running.