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About

I get companies named in AI answers.

Ten years building multilingual content systems, first in consumer tech, then in European fintech. The job was always the same: structured content that machines read correctly, at scale, in more than one language. AI visibility is that job with a new machine on the other end.

James Finlayson

Buyers now shortlist vendors inside ChatGPT, Claude, Perplexity and Gemini before they visit a website. If the answers do not name your company, you are not on the shortlist, and nobody tells you why.

I find the answers you are missing from, then fix the reason. Most of the market sells a dashboard that reports the problem. My work is the part after the dashboard.

How I work

Nothing invented. Questions come from real search and answer data. Every figure traces to a source, and anything unverifiable is flagged, not published.

Every recommendation carries the reason and a change-risk rating, because in a regulated firm someone has to explain why a change was made. Measured before and after: the same questions re-run on the same engines, so improvement is demonstrated, not claimed.

Who I work with

Finance. Fintech, payments, wealth and insurance, and the finance function inside companies in any industry. I also build compliance-grade AI systems, self-hosted and EU-resident, for firms that want AI they control rather than AI they rent.

What ten years taught me

Four things I did not believe at the start, and now do. The employment history behind them is on LinkedIn, with the names attached.

The problem is structural, not editorial

Most AI invisibility comes from structure the engines cannot read, not from prose they did not like. I learned that building content systems for a global consumer technology company, where structure was the whole job.

Multilingual is not a translation layer

AI answers differ by language in ways translation does not fix. I built the tooling behind a European fintech's visibility programme across four markets and four languages.

Measurement only counts if it reaches pipeline

Mentions are not the metric. On a cross-border payments programme we joined visibility to conversion data, so the question became which answers are worth appearing in.

In regulated work, compliance sets the architecture

I have built systems where data residency and GDPR drove the design rather than followed it. That is a different discipline from adding a cookie banner at the end.

Full background and client history on LinkedIn

See where you stand.

The same check the accountancy firm got, on your domain. About a minute. Costs nothing.