The evaluation happens without you
Docs, comparisons, forums, review sites. If a model cannot read your documentation, you are absent from an evaluation you never knew was happening.
Your buyer researches for six weeks before they contact you, and increasingly they do that research by asking an AI.
In short: Technology buyers self-educate. By the time they speak to you the shortlist is made — and that shortlist is now frequently assembled by a model reading documentation, comparisons and third-party discussion.
We build for technology businesses specifically — the agent is trained on your services, prices and policies, and the guardrails are set for your category rather than borrowed from a generic template.
Docs, comparisons, forums, review sites. If a model cannot read your documentation, you are absent from an evaluation you never knew was happening.
Well-structured technical documentation is exactly the kind of specific, factual, citable content models prefer. Most companies treat it as a cost centre.
People search "X vs Y" and ask assistants the same. If you do not write an honest comparison, someone less scrupulous writes it for you.
Technology companies build modern SPAs, and most AI crawlers do not execute JavaScript. This category is disproportionately invisible for exactly this reason.
Same agent, trained on your practice, your fleet, your floor or your book — not on a generic template for your category.
| Where we would start | The website agent, then AEO — fastest proof on traffic you already have |
|---|---|
| Phase 1 workstreams | Agent, organic social, paid, AI advertising, AEO, GEO, translation |
| Phase 2 | Automations ranked by payback, once Phase 1 has measured the business |
| Languages | Whatever your market speaks — Spanish first in most of Southwest Florida |
Technology buyers do not behave like local buyers, and geography matters far less than documentation does. The evaluation happens entirely without you — docs, comparison pages, forums, review sites — and it is increasingly assembled by a model reading those sources rather than by a person opening ten tabs. This category is also the most likely to be structurally invisible: modern single-page applications render content with JavaScript, and most AI crawlers do not run it.
Two weeks establishing what you actually sell, at what price, under what policies, and what your customers genuinely ask before they buy. This becomes the knowledge base the agent answers from and the source the answer engines read.
Usually on the website first, because it works on traffic you already pay for and proves the value before another dollar of media is spent.
AEO and GEO work on the site and off it — structured facts, answer-shaped content, crawler access, and consistency across every directory a model might check.
Paid and AI advertising switch on once there is something worth sending people to, and once the transcripts have shown what actually converts.
Being the business an AI names when someone asks about technology in your city — and being described accurately when it does.
How GEO worksA content engine that builds recognition, and paid media measured on what a customer actually cost rather than on clicks.
The content enginePaid placement inside the assistants, while the inventory is early and the competition in your category has not arrived.
Why nowSometimes, which is why it is grounded in your documentation and instructed to say "I am not certain, let me get someone" rather than improvise. For technical buyers a confident wrong answer is far more damaging than an admitted gap, so the guardrails here are tighter than in most other categories.
Possibly, and it is worth checking rather than assuming. If content only exists after JavaScript executes, a large share of AI crawlers see an empty page. Server-side rendering, static generation or prerendering fixes it. This is one of the first things we audit for technology clients because the impact is so large.
Tell us what your version of this problem looks like and we will tell you where to start.