AI discoverability service
Generative Engine Optimization
When someone asks ChatGPT, Gemini or another AI system about your company, does it understand the right facts? Generative Engine Optimization is the practice of making a company’s verified knowledge accurate, structured and citable, so AI systems can understand and correctly represent it. The methodology follows six stages: Discover, Understand, Verify, Trust, Cite, Recommend, and it puts authority before amplification.
What changed
Buyers increasingly ask an AI system before they visit a website. The AI answers by assembling something from whatever it can find and attribute. If your company’s public knowledge is thin, inconsistent, or contradicted across sources, the answer gets assembled anyway — from whatever was available.
The failure is not invisibility. It is being described incorrectly, confidently, to someone who never sees your site.
The six stages
Six stages, run in order. Authority comes before amplification, so the first three establish what is true and the last three make it findable and keep it that way.
- 01
Discover
Find what AI systems currently say about the company, and where it comes from.
- 02
Understand
Establish what is actually true — the entities, the products, the relationships.
- 03
Verify
Check each fact against a source that can be cited, and mark what cannot be supported.
- 04
Trust
Make the authoritative source unambiguous, structured and consistent across languages.
- 05
Cite
Give AI systems something specific and attributable to quote.
- 06
Recommend
Monitor how the company is represented, and correct the source when it drifts.
Authority before amplification
Each rung rests on the one beneath it. Publishing more content before the knowledge underneath is correct multiplies contradictions rather than authority — which is why the order matters more than the volume.
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Official website
One place the company controls and stands behind.
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Verified company knowledge
Each fact checked against a source that can be cited.
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Structured entities and relationships
What things are, and how they relate, in a form a machine can read.
-
Authoritative content
One clear answer per question the buyer actually asks.
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External authority
Corroboration from sources the company does not control.
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Distribution
Reach, once there is something correct to reach with.
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AI visibility monitoring
Watch how the company is represented, and correct the source when it drifts.
We run our own site this way
mportsco.com is built the way the methodology describes: every factual sentence resolves to a verified claim with a named source, each buyer question has one canonical page in both languages, and structured data only contains facts that also appear on the page.
That is what makes a company legible to an AI system: one answer per question, facts that can be traced, and nothing published that cannot be supported.
- One canonical answer per buyer question, per language
- Facts resolved from a governed registry, not written into a page
- Structured data that cannot contain a fact the page does not show
- A visible record of what we decline to claim
What no one can promise
We will not promise a ranking, a position in any AI system’s answers, or a visibility figure. Nobody can control what a generative system outputs, and a promise of that shape would be exactly the kind of unsupported claim this practice exists to remove.
What the work does is make the accurate answer easy to find, verify and attribute. Whether a given system uses it is not ours to guarantee.
Questions buyers ask
How is GEO different from SEO?
SEO optimizes for a ranked list of links. GEO optimizes for being understood, verified and correctly quoted by a system that assembles an answer. The overlap is real but the failure modes differ: an SEO problem is being ranked low, a GEO problem is being described wrongly.
Do we need to publish more content?
Usually not first. Publishing more before the underlying knowledge is correct and consistent tends to multiply contradictions. Verify, then publish.
Can you guarantee we appear in ChatGPT?
No, and we would be suspicious of anyone who does. What we can do is make the correct answer available, structured, and attributable.