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Outcomes over artefacts
A deck is not a decision; a demo is not a system. We measure ourselves on what makes it into production and what it changes.
The Founding Five Cohort: five founder-led client places for 2026, Navigator and above.
See the cohortAbout Vaer AI
Vaer AI was founded on a simple observation: enterprises are handed AI tools and dashboards, then left to do the work themselves. The software is cheap; the expertise to act on it is what's missing — and what actually wins.
So we built the opposite of a platform. A small, senior team that delivers the data and a dedicated analyst who takes action — for the price incumbents charge for software alone. We work with enterprises only.
Tom Wells — founder and principal consultant
Tom Wells is founder and principal consultant of Vaer AI, a research-led enterprise consultancy for AI search. He has previously played a leading role in AI research at market-leading companies, and has over a decade of experience working with the world's best brands.
Tom built Vaer AI to close the gap between GEO platforms that only monitor and consultancies that only interpret. His thesis is that small prompt sets can monitor movement but only large-scale research explains a market, and that enterprise teams shouldn't have to pay twice, once for a platform subscription and again for the consultants who read it. Vaer AI's model bundles measurement, competitor and citation research, custom research workstreams, and senior interpretation into a single engagement.
Tom works directly with every Vaer AI client, running large-scale AI search measurement across every major model, competitor and citation research, and founder-led strategy for a small number of enterprise teams. In 2026 he is running the inaugural Founding Five Cohort of five enterprise clients alongside the consultancy.


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A deck is not a decision; a demo is not a system. We measure ourselves on what makes it into production and what it changes.
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No staffing pyramid. The people doing the discovery are the people doing the implementation. It costs more per head; it costs less per outcome.
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Most AI projects fail because nobody agreed what "good" looks like. We define evals first, then choose the stack — not the other way round.
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Every engagement ends with a hand-off. Playbooks, hiring profiles, eval harnesses. We measure success by how quickly your team can run without us.
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