AI & GEO SEO. Rank on Google. Get cited by AI.

GEO is the practice of getting your business cited inside AI-generated answers — ChatGPT, Google AI Overviews, Gemini, Perplexity and Copilot. Where SEO competes for a position in a list of links, GEO competes to be one of the sources the model quotes while writing its answer. It relies on structured data, clear entity signals, third-party citations and questions answered directly and early on the page.

SEO optimises for ranking a page in a list of results. AEO optimises for being the single direct answer — featured snippets, People Also Ask, voice assistants. GEO optimises for being cited inside an answer the AI writes itself. AIO is an umbrella term that, in practice, usually means Google's AI Overviews specifically. They overlap but they are not interchangeable: they need different work and they are measured differently.

Four things, in order. Make the site machine-readable: structured data, clean HTML, and AI crawlers explicitly allowed in robots.txt. Answer real questions directly, with the core answer in the first 40–60 words. Build entity clarity so the model knows who you are and what you do. Then earn third-party mentions, because models weigh what other sites say about you. There is no submission form and no paid placement.

Most Indian agencies charge ₹25,000–₹2,50,000 a month, with starter programmes typically ₹25,000–₹50,000, and very few publish a rate at all. Ours starts at ₹15,000/month for the bundled Google-plus-AI-search retainer, rising to ₹30,000 and ₹60,000 as engine coverage and content volume increase. Those three numbers are the actual numbers — same for every client, month to month, no lock-in.

Yes, and it is still where most of the traffic is. But it is shrinking: Gartner forecast a 25% fall in traditional search volume by 2026, and AI Overviews now reach over two billion users a month. The pages that get cited by AI are usually pages that were already technically sound, so the two layers reinforce each other. Dropping SEO for GEO would be a mistake; running SEO alone is the more common one.

No, and you should be sceptical of anyone who does. Nobody controls what a language model outputs, and citation sets shift between model versions — this is even less controllable than Google rankings, where we also refuse to promise positions. What we guarantee is the work, the measurement, and a monthly record of which prompts name you and which name a competitor.

llms.txt is a plain-text file at your site root that summarises what your organisation does and which pages matter, written for large language models rather than search crawlers. It is a proposed convention, not an official standard, and it is not a ranking factor. It is cheap, it makes your positioning unambiguous, and it costs nothing to be wrong about. Ours is live at tnxn.agency/llms.txt.

We maintain a list of the buying questions that matter to you — 10 on Foundation, 30 on Growth, 75 on Authority — and run them against each engine your tier covers on a fixed schedule. The report records whether you were named, which URL was cited, and who was named instead. It is the same method you can run by hand; we just do it consistently and keep the history.

Better than you can on Google, usually. 77% of sources cited by AI assistants have a domain authority under 50, and in one large study over 33,000 of 48,560 cited domains appeared fewer than ten times each. Models reward specific, well-structured answers to narrow questions — which favours a focused local business over a broad national brand on exactly the queries you care about.

Honest answer: technical and schema fixes are often reflected within 2–6 weeks, because they change what the crawler can read. Genuine citation share on competitive commercial questions takes 3–6 months, and it moves in steps rather than a smooth curve as models refresh. Anyone quoting 30 days is selling you something. You see the audit and the work in month one either way.