Who it is for
- Businesses in a category people now research by asking an assistant.
- Teams who want to be in the answer, and cited as the source, not only listed as a link.
- Anyone who already invests in search and wants the second surface covered too.
Answer engines
Be the source the AI quotes.
Search is splitting in two. Half your future buyers will never see a blue link — they’ll read an answer an AI assembled. GEO is how you become the page that answer is built from.
- Answer-first pages
- Schema, FAQ markup and llms.txt
- Monthly LLM audits
- askedWhat should I look for when choosing a provider in this category?
- answerStart with three checks: scope, proof and how recently the information was updated [1] [2].
[1]your-site.example
[2]other-site.example
[3]third-site.example
- citedYour page is one of the sources the answer is built from.
Illustration: example data, not a customer.
What is generative engine optimization?
Generative engine optimization (GEO) is the work of making your pages the ones that AI assistants like ChatGPT, Perplexity, Claude and Gemini quote when they answer a question — and checking, every month, whether they do.
What it is not
- A replacement for SEO. It is a second surface, and the same structure usually helps classic search too.
- A promise that an assistant will quote you. We make pages easier to cite and measure what actually happens.
- Keyword stuffing. Answer engines reward clarity, structure, freshness and verifiable provenance.
Is GEO the same as SEO?
If your category is one people now research by asking an assistant, the question is no longer “where do we rank?”
Classic SEO
- Optimizes to win a position in a list of links.
- The question: where do we rank?
- The reader sees your link, then decides whether to click.
Generative engine optimization
- Optimizes to be the source a language model pulls into its answer.
- The question: when someone asks about this, are we in the answer, and cited as the source?
- Rewards clarity, structure, freshness and verifiable provenance over keyword density and backlink volume.
How it works
How does a page get cited in an AI answer?
A cycle that repeats every month: ask, read, change, ask again.
- 1. Someone asks. Buyers put the question to an assistant instead of scrolling a list of links.
- 2. An answer is assembled. The model pulls in sources and writes one answer. Clear, structured, current pages with visible provenance are easier for it to use.
- 3. Your page is cited, or not. We query the major assistants with the prompts your buyers actually use and track whether you appear, how you are described, and who gets cited instead.
- 4. We change what is in your control. Answer-first structure, schema.org and FAQ markup, an llms.txt, last-updated stamps. Then we ask again.
What do we change on your site?
Seven are changes to your pages and your measurement. The last one is why it pays off twice.
Answer-first pages
We restructure key pages so the claim is up top, the support is beneath, and the caveats are explicit.
Structured data
Clean schema.org structured data tells machines what each page is and who stands behind it.
FAQ markup
Real questions with short, direct answers, marked up so an answer engine can read and reuse them.
An llms.txt file
A plain file that tells AI crawlers exactly which pages are your source of truth.
Freshness and trust signals
Last-updated stamps, author and provenance signals show an engine that your page is current and authoritative.
Consistent names
Consistent entity naming, so your business, products and people are described the same way everywhere.
Monthly LLM audits
We query the major assistants with your buyers’ real prompts and track whether you appear and how you are cited.
Better for people too
The same answer-first, well-structured pages also tend to perform better in classic search and convert better for humans.
What you receive
A monthly audit of what the assistants actually say
GEO only matters if it shows up in the answers. Each month we ask the assistants your buyers use, and write down what came back.
- Whether you appear in the answer at all.
- How you are described, in the assistant’s own words.
- Who gets cited instead, so you can see what to fix.
- What changes next, as a short list tied to named pages.
Illustration: example data, not a customer.
4assistants asked
3mention you
2cite your page
- citedChatGPT: your guide is a source for the answer
- namedPerplexity: mentioned, not linked; description out of date
- absentClaude: not in the answer; another site cited instead
- citedGemini: your guide is a source for the answer
- nextMove the direct answer to the top of the guide
- nextRefresh the last-updated stamp and the entity name
From first call to a source worth quoting
Four steps, in this order. Every step has a plain-language output.
- 01
Diagnostic
We audit your site and your AI visibility: which prompts you appear in, how you are described, and who gets cited instead.
- 02
Scope
A fixed scope: which key pages get restructured and which machine-readable pieces are added, in what order.
- 03
Build or operate
We restructure pages answer-first, add schema.org and FAQ markup and an llms.txt, and add freshness and provenance signals.
- 04
Measure and improve
Monthly LLM audits compare results to the diagnostic baseline. Winners get support; losers get fixed or cut.
Pick the model that fits
Terms are stated up front, in the scope.
Project build
A defined website or system, built and launched with measurement in place.
Managed growth
Ongoing operation and improvement with an accountable operator.
Diagnostic or advisory
A focused audit and roadmap you can run yourself or hand to your team.
Product implementation
Setup and tuning of Avakata products inside your existing stack.
The longer version
Ranking and being cited are different games
Classic SEO optimizes to win a position in a list of links. Generative engine optimization optimizes to be the source a language model pulls into its answer. The mechanics differ: answer engines reward clarity, structure, freshness and verifiable provenance over keyword density and backlink volume.
If your category is one people now research by asking an assistant, the question is no longer “where do we rank?” It is “when someone asks about this, are we in the answer, and are we cited as the source?”
How we make you citable
We restructure key pages to be answer-first: the claim up top, the support beneath, the caveats explicit. We add the machine-readable layer: clean schema.org structured data, FAQ markup, and an llms.txt that tells AI crawlers which pages are your source of truth.
Then we make trust legible. Last-updated stamps, author and provenance signals, and consistent entity naming tell an answer engine that your page is current and authoritative.
Measured, not hoped
We run monthly LLM audits: querying the major assistants with the prompts your buyers actually use, and tracking whether you appear, how you are described, and who gets cited instead. That turns “AI visibility” from a vibe into a tracked metric you can move.
It compounds with everything else: the same answer-first, well-structured pages also tend to perform better in classic search and convert better for humans.
MonthlyLLM visibility audits
SchemaStructured data and llms.txt
Answer-firstClaim up top, caveats explicit
Free first step
Check your pages’ basics for free
Pulse is Avakata’s free snippet. Its SEO sentinel audits every page on every visit against eight search-engine basics and reports the problems it finds in your own portal. It sets no cookies. It is not a Google Analytics replacement, and it does not promise rankings or AI citations.
- auditChecks every page on every visit
- reportLists the SEO problems it finds
- freeFree, forever, no cookies
Frequently asked questions
Is GEO a replacement for SEO?
No — it’s a second surface. The good news is that answer-first structure and clean provenance usually help classic search rankings too.
How do you prove it’s working?
Monthly LLM audits: we query the major assistants with your buyers’ real prompts and track whether you appear and how you’re cited over time.
What do you actually change on the site?
Answer-first content structure, schema.org + FAQ markup, an llms.txt, and freshness/provenance signals like last-updated stamps and consistent entity naming.
What is generative engine optimization?
Generative engine optimization (GEO) is making your pages the ones that AI assistants use when they build an answer. It means answer-first page structure, schema.org and FAQ markup, an llms.txt file and visible freshness signals, then measuring the result in the assistants themselves.
Which assistants do you check?
We query the major assistants, including ChatGPT, Perplexity, Claude and Gemini, with the prompts your buyers actually use.
Do you promise I will be cited?
No. We make your pages easier for answer engines to cite, and the monthly audit shows what actually happened. Nobody controls what an assistant says.
Where does Pulse fit?
Pulse is a free snippet whose SEO sentinel audits every page on every visit and reports the problems it finds. It is a way to see page-level basics before an audit. Read more on the Pulse page.
What does it cost?
Price depends on scope, and scope depends on what the diagnostic finds. After a diagnostic you get a fixed scope and a fixed price for that scope, before any build begins.
Bring your funnel. We’ll show you where this would act.
Thirty minutes, screen-share, no slides — the person who built the engine walks you through what it would do on your site.