Services
Start with the audit. What follows depends on what it finds.
Each of these is one part of the loop, sold on its own. What you need depends on what the audit finds. The run tells you which one you're in, and the work below follows from that. The programme and advisory engagements sit outside that ladder and answer a different question.
AI visibility audit
If you're absent from the answers
Your buyers' real questions, put live to ChatGPT, Claude, Gemini, Perplexity and Google AI Overviews.
You get every question, every answer in full, who was named, who was cited, and the specific reason it was not you. Every figure traces to its run.
Outcome
A findings list you can act on, hand to your agency, or bring back to me.
AI visibility fixes
If you're cited but not named
Fixing the causes the audit found.
Content, structure, schema and internal linking rebuilt so the engines can read you, trust you and quote you. Measured against the same prompts each month and joined to pipeline rather than to mentions, so you can tell which visibility is worth having.
Outcome
Movement on the answers that matter, evidenced monthly.
AI content engine
If you're named but never cited
Producing the content the engines cite, at volume, in four languages.
Monitoring tools tell you that you are invisible and stop. This is the generation side: briefs grounded in real search and answer data, drafted in your voice, fact-checked before publication. Nothing invented, every claim verified or flagged.
Outcome
Published work that earns citations rather than impressions.
AI automation for finance teams
AI you control, rather than AI you rent.
Agents, assistants and automations running on infrastructure you own. Hosting, data residency and regulatory obligations are settled before the architecture rather than after it, because in a regulated firm those constraints decide the design. Your data stays in your estate and no model provider sees it.
- Workflow automation across the systems you already run
- Assistants over your own documents and data, hosted in your estate
- Connecting internal tools to AI assistants so they can be queried directly
- Migrating an existing AI workflow off a third-party platform
Outcome
AI in production without a compliance argument attached.
Advisory
AI transformation for finance
Your move to AI, planned and delivered, with the compliance question settled before the build rather than after it.
Where AI earns its place across the finance function, in what order, and who owns each part. The assessment names the workstreams worth doing, sequences them by risk and return, and delivers the first of them in production. Data residency and regulatory obligations shape the design from the start, because in a regulated firm they decide it.
- An AI operating model for the finance function, with ownership and guardrails
- A roadmap sequenced by risk and return, not by hype
- The first workstreams delivered in production, not a slide deck
- The compliance and data-residency position documented before anything ships
Outcome
AI in production across the finance function, on a footing that survives audit.
Fractional Head of AI Visibility
Senior ownership of how AI describes your firm, without a full-time hire.
One accountable person for the answers ChatGPT, Claude, Perplexity and Gemini give about you: what to fix, what to build, what to publish, and how each is measured against the same buyer prompts every month. The seat sits across the CFO office and marketing and holds the outcome, rather than handing over a dashboard.
Outcome
One owner moving the AI answers that matter, month on month.
Questions
Do you charge a day rate?
Do we have to take everything?
Which languages do you work in?
What is private AI, and do you build it?
Can we self-host the LLM, or does it have to be an API?
How is this different from an AI visibility tool?
Start with the audit.
It tells both of us whether there is enough to work on, and it costs you nothing.