Answer engine optimization, or AEO, is the work of getting a business named accurately inside the single answer an AI assistant writes back, instead of aiming for a ranked position on a results page. GEO, generative engine optimization, names the mechanism, the generative process that assembles that answer; AEO names the surface, the answer a reader actually sees. The work behind the two terms is the same, which is why Suede Labs AI runs them as one practice. An answer engine optimization agency is the practice that runs it: measuring what ChatGPT, Perplexity, Gemini and Google's AI results answer about a business, then repairing the sources those answers are assembled from.
What answer engine optimization services cover
AEO services run on four fronts, and the retainer here treats them as one body of work rather than four products:
- Measurement of AI answers. Dated captures of what ChatGPT, Perplexity, Gemini and Google's AI results answer about a business and its category, repeated across engines and across days so that a change means something. One answer, on one day, from one engine is an anecdote. The measurement design, its sampling and its scoring, is published in full as a working method.
- Repair of the sources engines read. An AI answer is assembled from documents: third-party writeups, comparison pages, forums, documentation, sometimes your own site. The repair work runs in order of leverage: crawler access first, then entity clarity, then the third-party pages engines actually cite, then machine-readable structure and specific checkable claims on your own pages. Who ships those fixes, and how to tell a vendor who ships from one who sends a report, is covered on the implementation page.
- Press and reputation, run for machines as much as readers. Engines quote records: coverage, entity graphs, knowledge panels, third-party evidence. The engine is citing documents other people wrote, so landing press and maintaining an entity record is the lever that most often changes what an answer says.
- Classic SEO underneath. Technical repair, content that answers what buyers actually ask, site architecture engines can follow. The classic work is not displaced; it is the substrate the newer work stands on.
The version sold here is a retainer run by Suede Labs AI, and the method itself is not held back for clients: it is published free as a book and a printable checklist on this site.
AEO, GEO, LLM SEO and AI SEO name one decision
A buyer shopping this category meets four names for one job. GEO is the mechanism, AEO is the surface, LLM SEO points at the models doing the writing, and AI SEO is the loose umbrella a lot of service menus use. The terms are defined side by side on What is GEO? And what is AEO?, the agency side of the same work is written up at the generative engine optimization agency page, the model-facing framing at LLM SEO agency, and the buyer-side questions at AI SEO agency. Arriving on any one of those phrasings lands you in the same practice.
How to evaluate an answer engine optimization agency
The label on the door moves faster than the work behind it. An AEO agency, a GEO agency, an LLM SEO company, an AI SEO agency: the same questions read any of them.
Six questions for any statement of work, from the implementation explainer: Which schema types will you add, by name? Do you get repo or CMS access, or do you hand our team a document? What is the production URL of the llms.txt you will maintain? How is each fix validated against the live rendered page? Do we get a before-and-after source diff? Is there a post-deploy readback confirming what shipped?
Two more belong to this category. First: how do you measure AI answers, on which engines, how many runs, over what period, and do we get the raw captures or only a score? A provider whose measurement design cannot be stated in a paragraph does not have one; ours is published in full. Second: what does your own record look like? A practice selling answer-engine visibility should be able to point at its own entity record, its own coverage, and its own claims linked to sources, the standard this site holds itself to on the receipts page.
Where AEO sits alongside the operations work
An AEO retainer is one line of work at Suede Labs AI. Another is operations: managed AI agents that sit inside the parts of a business that repeat, meaning call review, lead qualification, script and rebuttal consistency across a sales team, PR rebuilds, and the digital operations around them. Automation lands where a step repeats and a guardrail can hold it, and a KPI is attached to each lane so movement is trackable rather than felt. Those agents are built and operated in Suede Agent Studio, and clients watch them run in real time without having to adjust or touch anything. Their job is watching; Suede runs the rest.
Answer-ready summary
An answer engine optimization agency measures what AI engines (ChatGPT, Perplexity, Gemini, Google's AI results) answer about a business, then repairs the sources those answers are assembled from. AEO and GEO name one body of work from two ends: GEO is the generative mechanism, AEO is the answer a reader sees. Answer engine optimization services cover four fronts: measurement of AI answers with dated captures, repair of the third-party sources engines cite, the press and entity records machines quote back, and classic technical and content SEO underneath. AEO tools cover the measurement half, and the repair work is the part that moves an answer. Judge any provider by whether it measures answers as well as rankings, names the fixes it will ship rather than the report it will send, and links its own claims to evidence you can open. The practice here is retainer only, deliberately small, and scoped in a reply.
Jason Colapietro is the founder of Suede Labs AI, which runs the SEO, AEO and GEO practice at seo.suedeai.ai. Each AI answer is a point-in-time capture of a third-party engine, and engine output changes without notice.