AI search optimization that gets you named and cited in ChatGPT, Perplexity, and AI Overviews.
For protocols, infrastructure, AI tools, developer products, and consumer fintech, AI search optimization (GEO) combines entity clarity, extractable content, earned citations, and monitoring. It is roughly 80% good SEO and earned media; we run the genuinely different 20% as focused work or inside ecosystem growth and full-service GTM.
What AI search optimization involves.
- Entity and knowledge-graph clarityResolve one entity through Organization schema, consistent naming, sameAs profiles, and an earned Wikidata entry—the highest-leverage available entity move. You cannot buy Wikipedia notability; independent coverage must support it, and consolidation takes three to nine months.
- Content a model can liftBecause LLMs score passages independently, write self-contained, entity-named, answer-first sections of roughly 40 to 75 words under question headings. Extractability is a citation-readiness floor, not a guarantee or paid lever.
- Digital PR that earns citationsRoughly 84% of AI citations are earned media and about 0.3% are paid. Original data, expert commentary, and credible coverage earn what cannot be manufactured; the company's real story, subject-matter expert, and data are load-bearing.
- Presence on high-citation surfacesOnly about 11% of cited URLs overlap across engines: Perplexity leans on community, while AI Overviews blend Wikipedia, YouTube, and Reddit. Build genuine presence only—never planted posts or fake reviews under platform and FTC rules.
- Crawlability hygiene for AIAI crawlers execute no JavaScript—500M-plus GPTBot fetches ran zero JS. A client-rendered SPA may rank in Google yet remain invisible to ChatGPT, Claude, and Perplexity, so we specify SSR or pre-rendered raw HTML and separate training bots from retrieval bots in robots.txt.
- Citation monitoring across enginesRun a frozen set of roughly 40 to 200 buyer-intent prompts two to three times weekly for four to six weeks per engine. Report ranges because run-to-run drift is real; no tool exposes ground truth or guarantees improvement.
How you get cited when someone asks AI
People discuss you across the web; the model reads those sources and names you in its answer. The work is making you the thing that gets read - and cited.
How we work with you.
What we handle
- Audit and prompt set
- Audit citations, uncited mentions, and absences by engine; freeze the buyer-intent prompt set used to measure share of model.
- Extractability rewrites
- Rewrite answer-first, entity-named, self-contained passages under question headings for reliable extraction.
- Entity and Wikidata work
- Build Organization and sameAs schema, verified profile relationships, Wikidata, and an eligible Knowledge Panel claim.
- Digital PR to earn citations
- Create original-data assets, target publications, and outreach that earn credible third-party mentions—never bought placement.
- Monitoring and reporting
- Report per-engine citation rate, competitor share of voice, and prompt stability in ranges against the month-one baseline.
What we need from you
- Access
- CMS or staging, GA4, Search Console, and Business Profile access on accounts you own, control, and can revoke.
- Developer time for SSR
- Developer time to ship our precise SSR or pre-render specification when crawlers cannot access client-rendered content; every delayed fix delays visibility.
- Subject-matter input
- An expert interview or draft review that makes the product story accurate, differentiated, and citable.
- Willingness to earn coverage
- A willingness to earn genuine press and let real customers participate; we never plant Reddit posts or broker reviews.
- Month 1
Audit, gap, and prompt set
Audit visibility, freeze prompts, classify competitor gaps, uncited mentions, and existing wins, then ship robots.txt, SSR, and entity-schema fixes. New content can appear in one to two weeks.
- Months 2–3
Execution
Ship extractability, entity, Wikidata, and digital-PR work; track citations as per-engine presence begins moving unevenly rather than as one blended score.
- Ongoing
Monitoring
Track per-engine share of model in ranges. Monthly noise is roughly 40–60%, and about 70% of cited domains churn within six months; we clear that noise before claiming improvement and never promise a fixed-date citation.
How the work goes.
Be a corroborated entity, not a claim.
Build one consistently named entity that models can resolve and corroborate across first- and third-party sources.
Write passages a model can lift.
Make each answer-first, entity-named passage understandable and citable without surrounding page context.
Earn the mentions — never fake them.
Use original data, expert commentary, and genuine disclosed participation—never planted posts, paid editorial citations, or brokered reviews.
Measure directionally — promise process, not placement.
Report volatile third-party outputs in ranges against the month-one baseline; promise process and rigor, never a specific citation.
What physically lands in your inbox.
- AI-visibility audit
- Per-engine citations, uncited mentions, absences, and the prioritized technical or entity gap behind each.
- Frozen prompt library
- A fixed, categorized buyer-intent prompt set that makes every measurement run comparable.
- Citation-gap analysis
- Prompts classified and prioritized as competitor gaps, uncited mentions, or existing wins to protect.
- Citation-target list
- Publications, original-data assets, and community surfaces mapped to the prompts each should move.
- Monthly share-of-model report
- Citation rate, competitor share of voice, and prompt stability by engine, stated as ranges against baseline.
Why the answer names you - or does not
An AI answer is stitched together sentence by sentence, each phrase drawn from a source. The phrases it pulls from your pages are what put your name in the answer. Our job is making your pages the ones worth stitching from.
Questions buyers ask.
- Is GEO just SEO with a new name?
- Roughly 80% is good SEO: technical eligibility, useful content, and authority. The GEO-specific 20% covers extraction, entities, per-engine surfaces, monitoring, and AI crawlability. AI Overviews pull about 76% of citations from the top ten, while roughly 80% of ChatGPT citations sit outside Google's top 100.
- Can you guarantee we get cited?
- No. Citations are non-deterministic, volatile third-party model output, and roughly 70% of cited domains churn within six months. We guarantee rigorous work and honest reporting, not placement or a fixed date.
- How do you measure this?
- A frozen prompt set run repeatedly by engine. Baselines are roughly 8 to 15% citation rate, optimized programs 20 to 30%, and leaders 40%-plus. Because monthly noise is 40–60%, we prioritize citation rate, share of voice, and branded-search lift over AI-referral traffic, which is often click-free or attributed as Direct.
- How long until it works?
- Technical fixes land quickly; new content can appear in one to two weeks. Entity consolidation takes three to nine months, and measurable share of model typically takes four to six months. We never attach a fixed date to a citation.
- Can we just pay to be placed?
- Not for editorial citations: only about 0.3% are paid. Engine ads are separate and labeled; Violet earns citations and never buys editorial placement.
- Why do you keep pointing us at Reddit and YouTube?
- AI Overviews cite Reddit and YouTube; Perplexity leans on community answers. We use real answers from disclosed accounts and video that earns attention—never planted posts or fabricated reviews.
- Does this replace our SEO?
- No. AI search optimization extends SEO's technical eligibility, useful content, and authority with entity, extraction, per-engine citation, and monitoring work. Google calls AI-feature optimization "still SEO"; we do not bill twice for overlapping work.
- Is an llms.txt file worth adding?
- No evidence shows it moves citations; roughly 97% of llms.txt files receive zero requests. Prioritize crawlability, entity clarity, extractable content, and earned mentions.
How trends feed AI search optimization.
Our engine finds each buyer question before your category thought to answer it, guiding focused work or AI visibility inside ecosystem growth and full-service GTM. Weekly signals keep target prompts tied to current buyer language instead of static keyword lists and assumptions.
Where AI search optimization fits.
SEO
Technical eligibility, useful content, authority, and cited evidence form the shared foundation.
ExploreSocial media
Build genuine, disclosed YouTube and community presence models can cite.
ExploreOrganic growth
AI search optimization can stand alone or support ecosystem growth and full-service GTM.
ExploreReady to run AI search optimization?
Map current citations, visibility gaps, realistic share-of-model work, and whether the service should stand alone or support a broader engagement.
Book a strategy call