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We engineer the entity, schema, and authority signals ChatGPT, Perplexity, Claude and Gemini use to decide who gets cited.
The engines we audit you against.
Six industries, six firsts. Every one of these started from no presence in the answer at all, and every one was measured over a single ninety-day window.
Every engagement starts with a free audit of how AI systems currently describe, cite, or omit your brand. Ongoing work is scoped from what the audit finds — no fixed packages, no surprises.
We test how ChatGPT, Perplexity, Claude, and Gemini answer the questions your buyers ask — and report where you are cited, where you are omitted, and exactly what to fix first.
Request the auditNewtation earns attention inside AI answers. InPromptAds pays for it — native placement inside AI assistants, starting with ChatGPT Ads. Same buyer, same surface, opposite mechanism.
Visit InPromptAds(opens inpromptads.com in a new tab)Citation-grade content — original research, data, and comparison frameworks written so AI systems can extract and cite them directly.
Entity and schema architecture — structured data defining who you are, what you do, and why you are credible, in the format AI systems verify.
Freshness maintenance — scheduled updates that keep key pages inside the window AI systems treat as current.
Third-party authority — earned presence in the industry sources AI systems check before they cite anyone.
Competitor gap tracking — monthly monitoring of how AI describes you versus competitors, with work targeted where they are cited and you are not.
How the work is scoped, what actually changes, and what can and cannot honestly be promised about being cited.
The audit answers most of this with your own data — where each engine cites you today, and where it names someone else.
Run the free auditIt is the work of engineering the entity, schema, and authority signals that ChatGPT, Perplexity, Claude, and Gemini use when they decide which sources to name in an answer. There is no results page to climb here — either the model names you inside the answer, or it names someone else.
SEO competes for a position on a page of ten links. GEO competes to be one of the two or three sources a model cites inside a single generated answer. The selection mechanism is different, so the unit of work is different — entities and verifiable claims rather than keywords and rankings.
No. Classic search still sends real traffic and we do not touch it. GEO addresses the growing share of buying questions that now get answered without anyone clicking through to a website at all.
B2B SaaS teams — usually founders, CMOs, or the marketing lead — in categories where buyers have started asking an assistant before they ask a search engine. If your buyers are not doing that yet, the audit will say so.
The audit, which is free and needs no call. It reports where each engine cites you today, where it names a competitor instead, and what is missing that would change that.
We ask them. The engines are tested directly with the buying-intent questions in your category, and we record which sources come back named and in what terms. The work is then aimed at the gaps that testing exposed, not at a generic checklist.
Five lines of work: citation-grade content written so it can be extracted and quoted, entity and schema architecture in the format AI systems verify, freshness maintenance that keeps key pages inside the window models treat as current, earned third-party authority in the sources they check, and monthly tracking of how you are described against competitors.
No, and it is worth being careful with anyone who does. Model behaviour is probabilistic, changes between releases, and is not controlled by any vendor. What is honest to promise is measurement: you will know where you are named, where you are not, and what moved after each cycle.
Per engine and per question, month over month — whether you are named, how you are characterised when you are, and which competitor is named when you are not. It is a monitored position rather than a single score, because a single score would hide the only part that matters.
Either. Most engagements run with us writing to your review, but the schema and entity work is the part that has to be ours regardless — it is where the format matters more than the prose.
The audit is free. Everything after it is scoped from what the audit finds — there are no fixed packages, because the work needed by a brand that is already cited well is not the work needed by one the models have never heard of.
One. The Newtation Authority Engine runs monthly and covers the five lines of work above, across twelve stages. It is the only thing we sell after the audit.
Not any more. Paid placement inside AI assistants is InPromptAds, a Newtation company, at inpromptads.com. The two are run separately on purpose: an agency that recommends earned work while profiting from the paid alternative is not giving you a straight answer about either.
Schema and freshness work surfaces fastest, because it changes what the models can read about you immediately. Earned third-party authority is the slow line and always will be. Expect the first meaningful deltas in the monitoring across a cycle or two, not a week.
No. The work happens in your existing stack and in the sources AI systems already check. Nothing here requires you to adopt a platform, install a script, or move your site.
You will already have the audit, so the call is spent on what it found rather than on discovery. If the honest read is that GEO is early for your category, that is what you will be told.
