Answer engine optimization services that do the work, not just the dashboard
We find out what AI assistants tell your buyers about your market, decide what has to change, and then do it: pages on your site, profiles on review sites and directories, mentions in the roundups AI quotes, and corrected facts. You approve; we execute. No long calls, no committee.
SAGEO is a done-for-you answer engine optimization (AEO, also called GEO) service. We measure what AI assistants tell your buyers, choose the changes most likely to get you recommended, and carry them out — on your site and on the third-party sites AI reads. You approve the plan and the publications; we do the rest and report every week.
What we do
An AI assistant recommends a product when the pages it reads for the buyer's question describe that product clearly and favourably. Some of those pages are yours. Most are not. So the work has four layers, and we cover all of them.
Your site, readable for AI
- AI crawlers allowed in robots.txt and through your CDN or firewall
- Key pages rendered without JavaScript
- llms.txt, structured data, sitemaps, Bing indexing
Facts AI can repeat
- One source of truth: pricing, plans, integrations, limits
- Wrong facts traced to the page they come from
- Fixed on your site and on the profiles you control
Pages shaped like answers
- Comparison, alternatives and "best X for Y" pages
- Answers to the sub-questions AI actually searches
- Use cases, integrations and help pages AI can quote
The sites AI cites
- Review sites, directories and marketplaces
- The roundups and articles AI quotes for your category
- Community answers, partners and "made with" mentions
Which of these matters most depends on your category. That is why every project starts with a measurement, not with a template: in our data, your own site supplies only 1–5% of the sources AI cites before a buyer knows your name, so for most companies the biggest gains are off-site.
Why a dashboard is not enough
There are good AI visibility tools. They tell you which prompts you are missing from and which sites get cited. Then the work lands on your team — and the hardest part of that work is not software:
- registering your company on review sites and filling the profiles properly;
- writing to the authors of the lists AI quotes, and following up;
- answering questions in communities as a real person from your company;
- editing what an AI drafted until it is worth publishing under your name.
We are built around that part. Agents do the measuring, research and drafting; people do everything that needs a person. You get the outcome of an agency without having to staff one.
How a project runs
- Measure. We put 50 to 400 questions your buyers ask — about the problem, the category, alternatives, your brand — to ChatGPT, Claude, Gemini, Perplexity and Google AI. We record who gets named, in what order, with which facts, citing which pages.
- Plan. Within two to three days you get a plan: a 90-day goal, five to ten hypotheses, and the first month of work. Approve it with one click, or change it.
- Execute. Every week we work through the hypotheses: pages for your site, profiles on the right platforms, outreach to authors, community answers, fact fixes. Anything published under your name waits for your approval.
- Re-measure. The same questions are asked again every week, so each change is tied to the answers it moved. A hypothesis that works is scaled to neighbouring questions; one that does not is dropped.
- Report. Every Monday: what we did, what changed in AI answers, what is next, and at most two questions for you.
What a hypothesis looks like
| Field | Example for a SaaS knowledge-base tool |
|---|---|
| Hypothesis | If we publish "Product vs Notion" and "Notion alternatives for teams" and get into three of the roundups ChatGPT cites for that question, ChatGPT will start naming the product in answers about Notion alternatives. |
| Today | Named in 0 of 12 questions about Notion alternatives; the main competitor is named in 9. |
| Work | Two pages for the site (drafted by an agent, edited by a person); a profile in the right review-site category (registered by a person); messages to the authors of eight roundups (sent by a person). |
| Metric and date | Mentions in the same 12 questions after 4 and 8 weeks. |
| Decision | Three or more mentions — extend to neighbouring questions. None — change the approach. |
Who does what
| Who | Responsible for |
|---|---|
| Project agent (one per client) | The plan, hypotheses, priorities, tasks for other agents and people, the weekly report. |
| Execution agents | Measurement, drafts of pages and articles, technical fixes, finding platforms and authors, draft outreach. |
| People | Everything that needs a person: registrations, profiles, sending and answering outreach, community posts from a real account, editing. |
| Human curator | Checks every plan, spot-checks publications, handles anything sensitive. |
| You | Give access if you want to (or we work through drafts), approve publications under your name, tell us what not to say. |
Working with us: fast, careful, without the meetings
Most of the cost of an agency is coordination: kick-off calls, weekly syncs, approval chains. We removed it.
- No mandatory calls. Everything arrives by e-mail (or Slack, Telegram, WhatsApp). Reply to any message and it reaches the project agent. A call is there if you want one, never required.
- One-click approvals. Plans and publications come with "approve" and "change" buttons. If you do not reply to a plan within 48 hours we start the work that does not publish anything under your name.
- Speed. The free check takes two minutes. A full plan takes two to three days. First drafts and first registrations happen in week one.
- Quality. Every plan is checked by a person. Every text is edited by a person before you see it. Every claim about your product comes from your own source of truth.
- Cost. Because agents do most of the repeatable work, you get agency-grade execution for much less than an agency retainer.
Paying partly from the customers we bring
If the project fits, we can take part of our fee as a share of revenue from the customers we bring, instead of a fixed amount. It keeps us focused on paying customers, not on mentions for their own sake.
The one thing that has to be settled first is how "our" customers are counted. We agree it in writing before we start, using the signals your stack already has:
- visits referred by AI assistants (chatgpt.com, claude.ai, gemini.google.com, perplexity.ai and others) that end in a signup or purchase;
- the "how did you hear about us?" answer at signup — AI is now a common answer;
- referral codes or landing pages used only in the placements we create.
It suits products where a customer can be traced from first visit to payment — most SaaS and online stores. It suits less well when sales happen offline or months later through a sales team.
What we measure and report
| Metric | What it tells you |
|---|---|
| Named rate | In how many buyer questions AI names you, per engine and per buying stage. |
| Position and framing | Whether you are the first recommendation, one of several, or a footnote — and how you are described. |
| Accuracy | Whether the facts AI repeats about you (price, plans, integrations) are correct. |
| Source coverage | For how many of the sub-questions AI searches your pages or your mentions are among the sources. |
| Competitors | Who is named instead of you, where, and which pages give them the edge. |
| AI referral traffic | Visits and signups from AI assistants, so mentions are tied to customers. |
Who it is for
SaaS companies and online brands whose buyers compare options before paying: B2B and B2C software, developer tools, apps, marketplaces, e-commerce. It works best when there is a category people ask AI about ("best X for Y", "alternatives to Z"). It is not built for businesses that sell only locally or only through tenders.
What we never do
- Fake reviews, paid reviews passed off as genuine, or review swaps.
- Fake personas, sock-puppet accounts or undisclosed promotion in communities.
- Hidden text for crawlers, cloaking, or content written to mislead a model.
- Publishing anything under your name without your approval.
These tactics can work briefly, and then they become the thing AI says about you.
Frequently asked questions
What does an AEO agency actually do?
It makes AI assistants name and recommend your product when buyers ask about your category. In practice that is four kinds of work: making your site readable for AI crawlers, getting your facts consistent everywhere, publishing pages shaped like answers, and getting your product onto the third-party pages AI cites — directories, review sites, roundups and communities.
How is SAGEO different from an AI visibility tool?
A tool shows you where you are missing and leaves the work to your team. We do the work, including the parts no software can do: registering your company on review sites, writing to the authors of the lists AI quotes, answering questions in communities from a real person on your team.
Do I need to join weekly calls?
No. You get a plan, approve it with one click, and get a short report every Monday: what we did, what changed in AI answers, what is next, and at most two questions for you. A call is there if you want one.
How fast will AI answers change?
Fixes to your own site can show up within days for engines that search the web live. Third-party mentions take weeks to get published and picked up. We re-measure every week, so you see which changes moved which answers instead of waiting for a quarterly review.
Can part of the fee depend on results?
Yes. For a fit project we take part of our fee as a share of revenue from the customers we bring. We agree up front how those customers are counted — AI referral traffic, the 'how did you hear about us' answer at signup, referral codes — so nobody argues about attribution later.
Will you post fake reviews or create fake accounts?
Never. Accounts on review sites and directories are created for your company, on your work e-mail, by a person acting on your behalf. Community answers come from a real member of your team, openly. Reviews come from real customers.
See the questions your buyers ask, who AI recommends, and the first three things we would change.
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