Generative Engine Optimization that ships measurable citation lift. Measurable. Not vibes.
Cite is a GEO platform built on the same primitives Aggarwal et al. (2023) used to define the field: track citation rate per query, optimize content for the features LLMs actually quote, repeat. No "AI visibility scores" pulled from nowhere.
Citation tracking + quality-gated writing. €99/mo.
By Ville Ylläsjärvi · Updated May 29, 2026 · Written & optimized by Cite
No successful citation observations are available to display for this page. An empty or unavailable measurement is not evidence of zero citations. Dated observations will appear here when available; there is no guaranteed time to a citation.
See your three pillars before you sign up.
Paste your URL. Cite names the three pillar topics you should own to get cited by AI search.
GEO is empirically measurable. Most “GEO tools” aren’t.
The term Generative Engine Optimization was coined by Aggarwal, Murahari, Rajpurohit, Kalyan, Narasimhan and Deshpande in their 2023 paper "GEO: Generative Engine Optimization" (arXiv:2311.09735). They ran 10,000+ queries against generative engines and benchmarked nine optimization strategies against a held-out test set. Three tactics produced statistically significant citation-rate uplift: adding cited statistics (+30–40%), quoting authoritative sources (+30%), and fluent, well-structured writing. Keyword stuffing did nothing. Adding citations to fake sources did nothing. The paper is the closest thing GEO has to a foundational measurement framework.
Most tools shipping under the "GEO" label today skip the measurement half. They generate content, slap an opaque "AI visibility score" on a dashboard, and call it optimization. That is not GEO. That is content generation with marketing copy. The Aggarwal methodology requires (a) a reference query set, (b) repeated sampling across engines, (c) a baseline, and (d) a delta you can attribute to a specific edit.
Cite implements that loop. ChatGPT and Claude take turns, one a day: each asks your tracked queries every other day, up to 30 queries a turn, the longest-waiting first. We record the first time one of them cites you, and we mark the third-party pages in those answers that mention you (earned media). Once you connect your own Google Search Console and Bing Webmaster Tools, we read their query-level impressions, clicks and position too. We hold the query set stable so you can attribute citation lift to specific edits. We score share-of-voice with a 95% confidence interval rather than a single-day snapshot, because LLM sampling is stochastic and a one-day "you got cited" is noise.
The writing engine uses one full-context writing pass, then an independent review that scores 0–100 and requests targeted fixes when needed. It is built around the Aggarwal-validated tactics: cited statistics, named-source quotes, and semantic structure. Generation and measurement are the same product because they have to be.
GEO vs AEO vs SEO.
Generative Engine Optimization (GEO) is the practice of optimizing content so generative AI engines — ChatGPT, Claude, Gemini, Perplexity, and Google AI Overview — retrieve, cite, and quote it in their responses. Coined by Aggarwal et al. (2023), GEO is empirically measurable: citation rate per query, sampled across engines over time, attributable to specific content edits.
Search Engine Optimization (SEO) optimizes for a ranked list of blue links. The signal is position; the action is a click. Twenty-five years of literature, well-understood.
Answer Engine Optimization (AEO) optimizes for a single synthesized answer — featured snippets, voice assistants, the AI Overview box. The signal is being chosen as the answer; the action is being read aloud or rendered inline. We cover AEO in depth on /answer-engine-optimization.
Generative Engine Optimization (GEO) is broader. It optimizes for any generative output that may cite, paraphrase, or quote your content — ChatGPT, Claude, Gemini, Perplexity, Copilot, plus the AI Overview answer surface. The signal is being part of the source set the model retrieves and quotes from. Some practitioners use GEO and AEO interchangeably; Cite treats GEO as the superset and AEO as the answer-surface subset. The optimization tactics overlap heavily — both reward citable statistics, named sources, and clean semantic structure — but the measurement surface differs.
See where the terms overlap, which measurements differ, and what evidence to check before choosing a workflow. Compare AEO, GEO and SEO →
Four tactics, all research-backed, all instrumented.
Citation density
The Aggarwal paper found cited statistics produced the largest single-tactic uplift. Cite’s independent review flags any factual claim without a named source and scores against a configurable citations-per-1000-words floor; flagged claims get sourced in the targeted-fix pass.
Authoritative quote-marking
Quoting recognized authorities (+30% in the paper) is more effective than paraphrasing them. Cite preserves direct quotes with attribution and the Voice-pass keeps your prose around them. The Authority Outreach queue (Pro) helps you earn the kind of named-source quotes models actually retrieve.
Schema and semantic structure
LLMs retrieve from indexes that respect schema.org Article, FAQPage, and HowTo markup. Cite generates valid schema for every published draft and validates it on save. Headings follow a strict H2/H3 hierarchy because retrievers chunk on them.
Cross-source verification
A claim cited by three independent sources is retrieved more often than the same claim in one source. Cite’s Concept Glossary tracks which entities and claims you own across your corpus and flags single-source claims as fragile. The Earned Media tracker watches for third-party reinforcement.
Five passes. One pillar article. Twelve minutes.
Each stage runs against the Aggarwal-validated tactics — cited statistics, authoritative quote-marking, semantic structure — and the gate sends below-80 drafts back through Critique → Rewrite.
Full-context write — voice profile + glossary + your facts, guardrails built in
- Write
- Independent review
- Result
Each pass is checkpointed — if anything fails, Cite resumes from where it stopped instead of restarting.
What a Cite article looks like next to generic AI.
The same writing task, twice: explain AEO to a B2B founder.
In today's rapidly evolving digital landscape, it's not just about ranking on Google anymore. Answer Engine Optimization is a game-changer for B2B founders who want to level up their content strategy.
We're excited to share that by leveraging AEO, you can unlock unprecedented visibility across AI engines. It's not just about being found — it's about being the answer. Through thought leadership and strategic content, you can position your brand at the forefront of this paradigm shift.
AEO work makes a useful answer easier to find, understand and cite. Start with the question a buyer is trying to resolve and publish an explanation with sources the reader can inspect.
Google Search Central says its existing SEO practices apply to AI Overviews and AI Mode. Making the page accessible helps it qualify for discovery; it does not guarantee that an answer will cite it.
Keep observations separate from promises.
These are interpretation rules, not cohort benchmarks. A measured result needs a source, a query set, a collection window and a sample count.
Publication, indexing and a citation are separate events. Record when each happens. We do not have a published cohort benchmark that establishes a typical time to first citation.
A quality score is an editorial check, not a probability of ranking or citation. Inspect the source material and approve the exact version before publication.
Report the successful-sample denominator, tracked queries, source and measurement window. Failed or missing checks are not proof of zero citations.
You can’t optimize what you can’t measure.
Cite records citations for your tracked queries from ChatGPT and Claude, plus your own Google Search Console and Bing Webmaster Tools, each with the date it was checked. ChatGPT and Claude take turns, one a day: each asks your tracked queries every other day, up to 30 queries a turn, the longest-waiting first. We compute share-of-voice with a 95% confidence interval over 30 days because LLM outputs are stochastic — a one-day citation is noise; a rate over many samples is signal. When a ChatGPT or Claude answer first cites your domain for an anchor query, Cite stamps the date and emails you.
Cite vs generic GEO tools.
One price. €24.90 onboarding credits month one.
€99/mo: citation tracking, quality-gated writing, Voice Operating Manual, concept glossary, first-citation alerts, authority outreach queue, and earned-media tracking. The €24.90 onboarding credit covers your first Voice Operating Manual extraction and your first long-form draft.
GEO questions.
Cite · Long-form Article Agent
Stop guessing whether your content gets cited.
Set your anchor queries, ship the first 5-pass draft, watch the citation rate move. €24.90 onboarding credits cover your first Voice Operating Manual and your first long-form draft.
Start with one real job. FeedSquad shows you the finished work before anything publishes, and you keep the final say.
Start with €24.90 onboarding creditResearching AEO instead? Read the Answer Engine Optimization framing →
€24.90 onboarding · 7 days · credits to month one