faltastik.com
Six-language AI platform whose visibility depends on entity clarity across languages and on content architecture that stays indexable at scale.
faltastik.com
Read the case study →GEO · AI Search
Generative Engine Optimization for AI Search
Generative Engine Optimization (GEO) is the practice of structuring a brand’s content, authority and digital presence so that AI-powered search and answer engines can discover, understand, reference and cite it. POI369 runs GEO as a program built on solid SEO: clear entity information, server-rendered content that machines can parse, evidence pages that support every claim, and third-party corroboration. No system guarantees a mention. The work raises the odds and makes them measurable.
Last reviewed September 14, 2026 · Reviewed by Ahmet Bulut
We optimise brands for visibility across
ChatGPT and ChatGPT search. Google AI Overviews and AI Mode. Gemini. Microsoft Copilot and Bing’s AI answers. Perplexity. And traditional Google Search, which still sends most of the traffic and feeds several of the systems above.
SEO gets you ranked. GEO gets you understood and cited. The two are not rivals: Google’s own guidance for generative AI features says the classic SEO fundamentals still apply, and that original, non-commodity content matters more, not less. A GEO program that ignores technical SEO is marketing. A technical SEO program that ignores how answer engines select sources leaves visibility on the table.
What answer engines actually need from a brand
Each item below is something we can audit, fix and measure.
A clear entity
One name, one legal entity, one location, consistent everywhere: website, structured data, LinkedIn, directories, partner sites. Ambiguity is the first reason a brand is skipped.
Content machines can read
The important text in server-rendered HTML, not behind JavaScript. Direct-answer passages a model can lift on their own. Headings that describe, not tease.
Evidence for every claim
“We are an AI agency” is a claim. A live AI product with a case study is evidence. Answer engines weigh evidence pages, so we build them.
Third-party corroboration
Directories, partner mentions, interviews and real backlinks that repeat the same facts about the brand. Not bought links; independent confirmation.
Crawler access and signals
AI crawlers allowed in robots.txt, Content-Signal declared, sitemap fresh, IndexNow notifying Bing and partners the moment something changes.
Measurement
A fixed prompt set run monthly across the engines: are we mentioned, are we cited, at what position, next to whom, and which source the engine used.
The POI369 GEO program
Baseline benchmark
Before touching anything we run the prompt set across ChatGPT, Gemini, Perplexity and Google AI Mode and record where the brand stands. This is the number everything is compared against.
Entity and technical layer
Organization, Person, Service and Article structured data linked into one graph. Canonical naming. Crawler rules, sitemap, hreflang, llms.txt, IndexNow. The site becomes unambiguous to machines.
Commercial and evidence pages
Pages that answer the questions people ask engines, each with a direct answer, real capabilities, real projects and honest Q&A. Case studies rewritten as evidence, not portfolio tiles.
Original content
Research, experiments, engineering write-ups and data the engines cannot get elsewhere. This is what earns citations. Commodity articles do not.
Authority and corroboration
Directory profiles with identical facts, partner pages that reference the relationship, founder profiles that connect person to company to expertise.
Monthly measurement and iteration
The benchmark runs again. We publish the method openly in our AI Search Lab and apply it to client programs.
What GEO is not
It is not a trick that makes a model mention you. Answer engines change their retrieval and ranking often, and nobody outside those companies can promise a placement. Anyone who guarantees inclusion in ChatGPT or Gemini is selling something else.
It is not stuffing “AI agency Tallinn” into fifty pages. Engines that summarise text are reasonably good at recognising text written for them rather than for people, and Google’s guidance is explicit that generative features rely on the same quality signals as search.
It is not a replacement for SEO. It is what SEO becomes when a large share of the readers are machines that quote sources instead of listing links.
Evidence from our own work
GEO is easiest to judge by looking at how a brand structures its own presence. This site is our first case.
isimsec.com
Programmatic content product where structure, quality control and internal linking decide whether a very large page set gets crawled and cited or ignored.
www.isimsec.com
Read the case study →karasugundem.com
Editorial publisher where speed and publishing architecture, the same fundamentals GEO builds on, drive organic reach.
karasugundem.com
Read the case study →Who this is for
B2B and professional services
Categories where buyers increasingly ask an assistant for a shortlist before they search. Being in that shortlist is the goal.
Brands with real expertise and thin visibility
Companies that know their field but have never structured that knowledge so machines can find it.
Multilingual and multi-market companies
Where entity consistency across languages is hard and matters most.
Teams that want numbers
A monthly benchmark rather than a promise. If the needle does not move, you will know, and so will we.
Questions we get asked
Can you guarantee that ChatGPT will recommend us?
No, and no one can. What we guarantee is a documented method, a measured baseline, and monthly numbers showing mention rate, citation rate and position across the engines. The program is judged on those numbers.
How is GEO different from your AI search optimization service?
GEO is the ongoing program: content, entity, authority and measurement over months. AI search optimization is the diagnostic and technical layer: an audit of crawler access, HTML, structured data and current visibility, plus the fixes. Most clients start with the audit and continue with the program.
Does llms.txt help?
It is a useful, machine-readable index of what the site is about, and we maintain one generated from the same content as the pages. It is not a ranking factor and it does not replace real HTML content. We treat it as a courtesy to crawlers, not as the strategy.
Do FAQ schemas still matter?
Google retired FAQ rich results in May 2026, so we no longer add FAQ structured data for its own sake. Real question-and-answer sections still help readers and give engines clean passages, which is why this page has one.
How long before results show?
Technical and entity fixes are picked up within weeks. Citation changes in answer engines typically take a few months and depend on how much original content and corroboration the program produces. The baseline benchmark makes the timeline visible.
Related expertise and reading
Related expertise
Related insights
GEO vs SEO: What Changes When the Reader Is a MachineGenerative Engine Optimization is not a replacement for SEO and not a new discipline invented by agencies. It is what search optimization becomes when the reader summarises and cites instead of listing links. Here is what actually changes, what stays the same, and where the money should go.ChatGPT Ads vs Organic Visibility: What Paid Placement Buys and What It CannotAn ad in ChatGPT rents a labeled card under the answer. It does not buy a place inside the answer, and it never reaches the subscribers who pay to avoid ads. What each side gets you, what the early data says about the overlap, and why we run the two as one program.How AI Search Discovers, Understands and Cites a BrandBetween a company’s website and a sentence in a ChatGPT answer there are four stages: crawling, retrieval, entity resolution and citation selection. Each one can silently drop a brand. This is a plain-language map of the pipeline and of what a brand controls at each stage.How to Improve Brand Visibility in ChatGPT and AI SearchA working checklist, in the order we apply it: measure first, open the doors, make the entity unambiguous, write passages an engine can lift, publish evidence, get corroborated, measure again. No tricks, no guarantees, and every step is something you can verify yourself.How We Structure Next.js Websites for Search and AI CrawlersThe concrete decisions behind poi369.com and the products we build: what goes in server-rendered HTML, how a page serves Markdown to agents on request, why sitemap dates are derived from content signatures, how six languages stay self-canonical, and how structured data forms one graph. Everything here is running in production.
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Find out where you stand in AI search
We run the baseline benchmark for your category and send the results with a written plan. No obligation to continue.