Founder, B2B SaaS
- PAIN
- Prospects say they 'asked ChatGPT for tools like ours' and never heard our name.
- SOLUTION
- Baseline the exact prompts, find which competitors get cited, and earn placement on the sources feeding those answers.
Search no longer ends on a results page. ChatGPT, Perplexity, Claude and Google's AI Overviews answer directly — and decide which brands get named. We measure how often the answer is you, and we move that number.
ChatGPT, Perplexity, Claude, Gemini, Copilot and Google AI — measured on the same schedule, not sampled by hand.
Every recommendation traces to a logged prompt and a captured answer. If we cannot show the citation, we do not claim the win.
You see who the models recommend instead of you, and on which prompts. That list is the work queue.
Most agencies sell you AI-written articles and call it GEO. We start by finding out what the models already say, then change the inputs they read.
We run your category's real buyer prompts across every major answer engine and record who gets named, cited and linked.
Answer engines read structured data and entity graphs before prose. We fix schema.org validity, entity linkage and machine-readable company facts.
Models cite the sources they trust. We identify which domains they draw from in your category and earn placement there.
Extractable claims, explicit numbers, clear attribution. Writing that survives summarisation instead of dissolving into it.
CiteLens re-runs your prompt set on a schedule so you see movement, not a one-off snapshot.
AI Overviews are built on the organic index. Technical SEO is not obsolete under GEO — it is the substrate.
A GEO engagement runs on the same discipline as our engineering work: measure, change one input, measure again.
We build your prompt set from real buyer language, run it across six answer engines, and record the starting share of voice.
≈ 7 daysWhich sources do the models cite for your category? Where does your entity data contradict itself? What are competitors doing that you are not?
≈ 14 daysStructured data validity, entity linkage, llms.txt, extractable claims. This is engineering work, and we do it in your codebase.
≈ 30 daysPlacement on the domains the models actually cite. Slow, unglamorous, and the part that moves the number most.
≈ 60 daysCiteLens reruns the prompt set. We report movement against the baseline, not vanity metrics.
By the time someone reaches your site, an answer engine has usually already given them a shortlist. GEO decides whether you were on it.
GEO advice is cheap. We run a production product that measures the thing we sell, and we use it on ourselves.
Our GEO visibility platform. It measures how often ChatGPT, Perplexity, Claude, Gemini, Copilot and Google AI mention and cite a brand — and shows who they recommend instead.
Verified travel intelligence for 42 countries, built on a zero-hallucination pipeline. The grounding discipline behind everything we claim about AI output.
Machine-readable company facts, a validated schema.org entity graph and a maintained llms.txt. The substrate work we sell is the substrate we run.
No retainer before we can both see the baseline. If the models already name you everywhere, we will tell you and you keep your money.
You do not know what AI says about you.
You know you are invisible and want it fixed.
GEO, SEO and engineering need to move together.
Our own product where it is best, third-party data where theirs is better.
What people ask before hiring a GEO agency.
A GEO (generative engine optimization) agency improves how often and how favourably AI answer engines — ChatGPT, Perplexity, Claude, Gemini, Copilot, Google's AI Overviews — mention and cite your brand. Where SEO optimises for a ranked list of links, GEO optimises for the generated answer itself.
SEO wins a position; GEO wins a citation. They are not rivals: AI Overviews are generated from the organic index, so technical SEO remains the substrate. GEO adds entity data, structured data, source placement and content the model can extract and quote.
Yes, and we insist on it. We build a prompt set from real buyer language, run it across six answer engines on a schedule, and record every mention, citation and competing recommendation. That is what our product CiteLens does. If we cannot show the captured answer, we do not claim the result.
Structured-data and entity fixes register within weeks, because models re-crawl the substrate. Source placement — earning your way onto the domains the models cite — takes months. We report movement against the baseline monthly, so you never wait blind.
No, and be careful with anyone who does. Model outputs are probabilistic and vendors change them without notice. What we guarantee is measurement: you will know exactly where you stand, what changed, and what caused it.
Because we build the measurement tool. CiteLens is our own production product, not a reseller dashboard. We also run the substrate work we sell — a validated schema.org entity graph and a maintained llms.txt on our own domain.
GEO rarely stands alone. These are the tracks it usually touches.
We will run your category's real buyer prompts across six answer engines and show you the baseline — before you commit to anything.