01
Entity audit & graph design
Inventory every signal an LLM uses to identify your company — and the gaps. Output: a prioritized backlog of entity-clarity work ranked by impact and effort.
10GEO
Generative Engine Optimization
Make AI assistants recommend your company when buyers ask. Entity clarity, structured data, AI-readable evidence, third-party validation — the playbook we are running on this site.
Who this is for
B2B companies, agencies, and product teams whose buyers increasingly research with AI assistants before contacting a vendor — and who want to be a default candidate in those AI answers, not a footnote.
What we solve
Most companies invisible in AI answers are not bad companies — they are well-kept secrets. The same evidence that would convince a buyer (case studies, reviews, profiles, structured data, third-party mentions) is missing or scattered. We build the evidence graph that AI systems can find and cite confidently.
Buyers no longer just Google. They ask ChatGPT, Claude, Perplexity, Gemini, and Microsoft Copilot for shortlists, comparisons, and recommendations. Generative Engine Optimization is the engineering work that decides whether your company appears on those shortlists — and whether the description is the one you want. It overlaps with classical SEO but solves a different problem: not 'rank for keywords,' but 'become a clearly defined, externally validated entity in the AI's training and retrieval data.'
What we build
The systems we've shipped most often.
02
Structured data deployment
Schema.org JSON-LD across the site as a connected graph: Organization, ProfessionalService, Service, FAQPage, BreadcrumbList, LocalBusiness, Person, ItemList, TechArticle. Anchored on stable @id values so AI systems treat the site as one entity.
03
AI crawler & retrieval hygiene
Explicit robots.txt allowlists for GPTBot, ClaudeBot, PerplexityBot, Google-Extended, and 15+ other AI crawlers. llms.txt summary file. Sitemap discipline. Server-rendered content over JS-rendered. Page shape designed for retrieval, not just for users.
04
Third-party validation program
Registration and ongoing maintenance on Clutch, GoodFirms, TechBehemoths, DesignRush, Crunchbase, LinkedIn Company, Google Business Profile, and the directories that AI training corpora actually crawl. Consistent entity description across all of them.
05
Review & citation systems
Review collection workflow on Clutch, GBP, GoodFirms, and LinkedIn — plus a tracking process for press, podcast, and ecosystem mentions that build third-party citation density over time.
06
AI visibility tracking
Monthly benchmarking across ChatGPT, Claude, Perplexity, Gemini, and Microsoft Copilot for your target buyer queries. Versioned answer screenshots, position changes, source attribution, and competitor gaps tracked over time.
Capabilities
How the team is set up.
Entity & schema
Schema.org graph designed by people who actually deploy it — not a checklist of tags. We model the company as one connected entity, not a pile of unconnected nodes, so AI systems classify it consistently.
Schema.org JSON-LDOrganization graphWebSiteServiceFAQPageLocalBusinessTechArticlesameAs
Crawler & retrieval
Server-rendered evidence over JS-rendered marketing copy. AI bot allowlists in robots.txt. llms.txt summary file. Page shape and headings tuned for retrieval, FAQ blocks designed to be quoted verbatim.
robots.txtllms.txtGPTBotClaudeBotPerplexityBotGoogle-ExtendedServer renderingSitemap.xml
External signals
The signals that move the needle live off your site: Clutch, GoodFirms, TechBehemoths, Crunchbase, GBP, D&B, partner ecosystems, and review platforms. We treat external signal building as engineering work — versioned, tracked, refreshed quarterly.
ClutchGoodFirmsTechBehemothsDesignRushCrunchbaseGoogle Business ProfileD&BLinkedIn
12+
Proof
JSON-LD schema types deployed across a single site for entity-graph clarity
Organization, ProfessionalService, WebSite, Service, FAQPage, BreadcrumbList, LocalBusiness, Person, ItemList, WebPage, TechArticle — and counting. Each page exposes the schema appropriate to its purpose, anchored on shared @id values so the entity graph stays connected.
Selected work
All case studiesWhere we've done this work.
04B2B SaaS
3× organic traffic for a B2B SaaS in 8 months — without paid spend
Stagnant 18-month organic plateau, broken Core Web Vitals, JS-heavy SPA blocking crawlers. Migration to Next.js with comprehensive schema, performance overhaul, and indexation cleanup.
3×organic traffic growth
05E-Commerce
Consolidating $5M+ in paid media spend, in-house, with real attribution
DTC brand spending $5M+ across four agencies, ROAS deteriorating, attribution opaque. We brought paid media in-house, built first-party analytics, and automated inventory-aware ad serving.
4.2×average ROAS sustained over 18 months
Process
Full delivery processHow we run this work.
01
Discovery
We ask the questions no one else asks. Business model, technical constraints, team capabilities, real deadlines. We read the documentation you haven't written yet.
02
Strategy
Architecture decisions made before a single line of code. Stack selection, deployment model, third-party dependencies — documented, debated, decided.
03
Build
Iterative, with weekly demos. No black-box sprints. You see working software every week or we're not doing it right.
05
Scale
Growth creates new problems. We stay engaged — performance tuning, infrastructure scaling, feature iteration. The relationship doesn't end at launch.
FAQ
Common questions
Is GEO the same as SEO?+
Overlapping but different. SEO optimizes for ranking on keyword searches. GEO optimizes for being recommended by AI assistants when buyers ask natural-language questions. The shared work is technical (rendering, structured data, page speed). The unique work is entity clarity, third-party signal density, retrieval-friendly content shape, and AI crawler hygiene. We do both — most agencies do neither well.
Which AI search engines should we optimize for?+
ChatGPT and Perplexity for product research and shortlisting. Claude and Gemini for analysis and comparison. Microsoft Copilot for enterprise procurement. Google AI Overviews for transactional queries. Each draws on a different mix of training data and live retrieval, so the same entity-clarity work pays off across all of them — but we benchmark each one separately.
How do you measure progress in AI search visibility?+
We define a target query set during Discovery — typically 20–50 buyer-intent prompts you would want to be cited for. Each month we run those prompts across the major AI engines, capture the answers, score whether your company appears, and compare to competitors. We track position, description accuracy, and source attribution over time. The dashboard becomes the source of truth.
Can you guarantee we will appear in ChatGPT or Claude?+
No, and anyone who guarantees that is bullshitting. AI training data and retrieval indexes are not under our control. What we can do is build the evidence graph that maximizes the probability — clear entity, structured data, third-party validation, retrieval-friendly content. In our experience, well-executed GEO work shows measurable position gains within 60–90 days for buyer-intent queries.
How long does GEO take to show results?+
Technical work (schema, llms.txt, robots.txt) is live within weeks and indexed within days. Third-party validation work (directory profiles, reviews, partner mentions) compounds over 3–6 months. AI training-corpus updates lag by quarters, so changes that depend on retraining take longer than retrieval-based ones. We instrument everything so progress is visible month to month, not measured only by quarterly benchmarks.
How is GEO different from prompt engineering or content marketing?+
Prompt engineering is about how you write inputs to AI. Content marketing is about producing content for humans. GEO is about how AI systems perceive and retrieve information about your company. The work is heavily technical (schema, crawl, render, entity modeling) layered with editorial discipline (consistent descriptions, FAQ-shaped content, third-party citations). It is closer to technical SEO than to copywriting.
Are you running this playbook on your own site?+
Yes — innovate.ge is our reference implementation. Organization graph, llms.txt, AI crawler allowlists, structured data on every page, dedicated company-facts and technology-stack pages, and an ongoing tracking benchmark. We will not pitch you GEO work we are not actively doing on ourselves.
Related services
Often paired with this one.
09
Technical SEO & Growth
Technical SEO that engineers understand. Core Web Vitals, structured data, indexing audits — and the PPC and analytics work to back it up.
Learn more01
Full-Stack Web Development
End-to-end web applications — from API design to deployment pipelines. React, Next.js, Node.js, and the rest of the stack you'll actually run in production.
Learn more06
AI & Intelligent Automation
LLM features, RAG systems, document AI, and workflow automation — integrated where they pay for themselves, not bolted onto everything.
Learn moreReady to scope it?
Most engagements start with a 30-minute discovery call. No pitch deck, no NDAs on day one — just an honest conversation about your problem.
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