Timothy DeVore — GEO Architect & AI Agent Platform
TIM is the AI agent platform of Timothy DeVore, GEO Architect and Fractional CIO/CTO. We build Knowledge Graphs and AI-ready infrastructure so LLMs cite your business as the authoritative answer.
TIM — Your Personalized A.I. Agent | Timothy DeVore GEO Architect
SEO Rents Traffic. GEO Owns the Answer. Timothy DeVore builds Knowledge Graphs and AI-ready infrastructure so businesses become the authoritative LLM citation.
Generative Engine Optimization (GEO) Architect
Timothy DeVore is a GEO Architect and Fractional CIO/CTO with a 30+ year career engineering enterprise-level AI, blockchain, and network infrastructure for organizations like FedEx and Visa. He is the founder of the Timothy DeVore GEO Firm and creator of the Technical Retrofit methodology for AI-ready entity authority.
Designs and engineers entity authority systems that ensure AI language models cite a brand as the authoritative answer to relevant queries.
A boutique Generative Engine Optimization firm specializing in the Technical Retrofit of legacy enterprise systems and Knowledge Graph engineering. We build permanent data assets so AI language models cite our clients as the authoritative answer.
The engineering-first discipline of structuring your business data — website schema, entity records, Knowledge Graph entries, and content format — so AI language models (ChatGPT, Perplexity, Gemini, Claude) select your brand as the authoritative answer to relevant queries.
Entity Verification & Knowledge Graph Setup
Timothy DeVore's proprietary Technical Retrofit methodology modernizes legacy CMS architectures with AI-ingestible data layers — adding JSON-LD structured data, entity verification, Knowledge Graph entries, and Answer Nugget content to existing websites without a full rebuild.
New website construction with AI-first architecture: JSON-LD schema on every page, entity-first content strategy, Knowledge Graph integration, and structured data that makes the site immediately legible to all major AI crawlers and language models.
Knowledge Graph & Entity Authority Engineering
Structuring your brand, expertise, and offerings as a single verifiable entity in AI Knowledge Graphs. Includes Wikidata entry creation, sameAs link network construction, Google Knowledge Panel optimization, and cross-source entity corroboration.
Beyond GEO — building the intelligent infrastructure that automates operations, connects systems, and deploys autonomous AI agents across the enterprise. Services include RAG pipeline construction, multi-agent orchestration, workflow automation, and AI-native operational systems.
T.I.M. (Technical Insight Machine) is the architectural backbone of the Timothy DeVore GEO and AEO strategy. T.I.M. performs Entity Mapping, Signal Optimization, and Answer-First Protocol auditing to ensure every site in the GPAN network achieves 100% LLM ingestion compliance.
GEO Frequently Asked Questions — Timothy DeVore
What is Generative Engine Optimization (GEO)?
Generative Engine Optimization (GEO) is the engineering-first discipline of structuring your business data — website schema, entity records, Knowledge Graph entries, and content format — so AI language models (ChatGPT, Perplexity, Gemini, Claude) select your brand as the authoritative answer to relevant queries. Unlike SEO, which optimizes web pages for Google's document retrieval system, GEO optimizes your entity data for AI answer generation systems.
What is the difference between SEO and GEO?
SEO (Search Engine Optimization) optimizes web pages to rank in a list of blue links returned by Google's document retrieval system. GEO (Generative Engine Optimization) optimizes your brand's entity data so AI systems cite you as the definitive answer. SEO rents traffic from an algorithm. GEO builds a permanent data asset that compounds in authority over time.
The Technical Retrofit is Timothy DeVore's proprietary GEO methodology for modernizing legacy CMS architectures with AI-ingestible data layers without requiring a full site rebuild. It adds JSON-LD structured data, entity verification records, Knowledge Graph entries, and Answer Nugget content to existing websites.
An Answer Nugget is a concise, self-contained paragraph of content — typically 40–120 words — written specifically to be quoted verbatim by AI systems. Answer Nuggets directly answer a specific question your target audience asks AI and are structured with a clear question signal and a complete, citation-ready answer.
A Knowledge Graph is a database of entities and the relationships between them. Google's Knowledge Graph contains over 500 billion facts about 5 billion entities. When AI systems generate answers, they query knowledge graphs to identify verified, authoritative entities relevant to the query.
AI Share of Voice is the percentage of AI-generated responses for a defined query set that include your brand as a cited, recommended, or mentioned source. It is the primary GEO performance metric, replacing traditional SEO rank-tracking.
The Silent Crisis: Why Being #1 on Google Doesn't Matter if Siri Doesn't Know Your Name
Your top Google ranking is a vanity metric in the age of AI. Discover why structured data and entity authority are the keys to being recommended by voice assistants like Siri and Alexa.
SEO vs GEO: Why Entities Are Killing the Blue Link
The blue link is dying. AI-generated answers have replaced ranked results for millions of queries. Learn why entity authority — not keyword ranking — is the currency of the next search era.
SEO Is Dead: Why Your Business Needs Generative Engine Optimization
Traditional SEO is no longer enough. AI-driven search has fundamentally changed how businesses get found. Learn why Generative Engine Optimization is the new standard for digital authority.
How to Build a Citation & Attribution Strategy for GEO (Generative Engine Optimization) That Gets Your Brand Referenced in AI Answers
Learn how to build a citation and attribution strategy for Generative Engine Optimization (GEO) that gets your brand referenced in AI-generated answers from ChatGPT, Gemini, and Perplexity.
SEO is Dead. Why Your Business Needs "Generative Engine Optimization"
Discover why traditional SEO is failing and how Generative Engine Optimization (GEO) is the key to surviving the AI shift in search behavior.
SEO vs. GEO: Why "Entities" Are Killing the Blue Link
The era of Search Engine Optimization focusing on keywords and backlinks is ending. The future belongs to Generative Engine Optimization (GEO), where visibility depends on establishing your brand as a trusted 'Entity' in the Knowledge Graph.
FAQ & Answer Nuggets: How to Build a Citation & Attribution Strategy for GEO (Generative Engine Optimization) That Gets Your Brand Referenced in AI Answers
What’s the difference between a mention and a citation in GEO?
A mention is when an AI answer names your brand, product, or person. A citation is when the answer explicitly references your source—often with a link, publication name, or quoted metric. Citations create durable “source memory” because systems can re-fetch and validate the claim, which increases repeat inclusion in future answers.
Do schema markup and structured data directly increase AI citations?
Schema rarely causes citations by itself, but it improves attribution reliability by clarifying entities, authorship, dates, and content types. Article, Organization, Person, FAQPage, and Dataset markup help retrieval systems disambiguate who wrote the content and when it was updated. The biggest gains come when schema supports highly extractable claims and clear methodology.
What kind of content is most likely to be cited by AI assistants?
Content with reusable claims: original benchmarks, clearly scoped definitions, step-by-step procedures, and comparison tables. AI systems prefer information that is specific, time-stamped, and easy to extract without ambiguity. Adding a concise methodology block (sample size, timeframe, inclusion criteria) increases trust and makes numeric claims safer to reuse.
How do I measure whether my GEO citation strategy is working?
Track “citation share” across a consistent set of prompts tied to your market and buyer questions. Log whether your brand is cited, merely mentioned, or absent, and record which specific claims were reused. Supplement with referral traffic from cited links, but prioritize in-answer attribution quality (correct brand, correct URL, correct claim) as the core KPI.
How long does it take to start getting cited in AI answers?
For most brands, mentions can appear within weeks once entity signals and definitions improve. Consistent citations typically take 2–3 months after publishing quotable assets with clear provenance, then accelerate once third-party corroboration builds. Competitive categories and regulated topics often require more corroboration and stricter sourcing, extending timelines to 3–6 months.
AI citations are won at the claim level, not the page level.
Generative answers extract and reuse small units of information—definitions, numbers, steps, and comparisons. Pages that present bounded, clearly scoped claims near their supporting context are easier to quote and validate. Designing content around reusable claims consistently improves attribution because systems can attach a source to a specific statement.
Methodology blocks make benchmarks safer for AI systems to reuse.
Numeric claims are frequently excluded when provenance is unclear. A compact methodology block—timeframe, sample size, inclusion criteria, and limitations—reduces ambiguity and increases trust. It also helps editors and secondary publishers repeat your metric accurately, creating corroboration that further increases the likelihood of AI citation.
Corroboration turns brand-owned facts into internet-validated facts.
When independent sites reference your data or framework and link to the canonical source, it creates agreement signals that models and retrieval layers can detect. This reduces the risk of relying on a single publisher and increases confidence in the claim. The result is a flywheel: more citations lead to more mentions, which lead to more citations.
Stable URLs and section anchors improve attribution precision.
AI systems often cite a page while extracting from a specific section. Descriptive headings, consistent anchor IDs, and canonical URLs make it easier to point to the exact claim being quoted. This reduces misattribution, improves the quality of citations, and increases the chance that future answers will reference the same authoritative section.
Editorial policy pages strengthen E-E-A-T signals for GEO.
An editorial policy documents how content is researched, reviewed, updated, and corrected. That transparency increases perceived reliability, especially for advice and benchmark content. When combined with named authors and credentials, it gives retrieval systems and human reviewers clearer trust signals, which supports more frequent and more accurate citations.
FAQ & Answer Nuggets: SEO is Dead. Why Your Business Needs "Generative Engine Optimization"
Is SEO really dead, or is this just hype?
The economic model of SEO — where ranking in Google reliably delivers traffic and leads — is being structurally disrupted by AI. 27% of US searches now generate AI Overviews that eliminate clicks. 14% produce zero clicks. 1.8 billion people use ChatGPT monthly. These aren't hype metrics; they're current adoption numbers that represent real customers who will never see your Google ranking.
Generative Engine Optimization (GEO) is the discipline of structuring your business data — your website's JSON-LD schema, your entity's presence across Knowledge Graphs, and your content format — so that AI language models like ChatGPT, Claude, and Gemini select your brand as the authoritative answer to relevant queries.
Local service businesses (plumbers, lawyers, dentists), professional services firms (consultants, accountants, advisors), and B2B companies in competitive verticals need GEO most urgently. These are the businesses where AI is actively replacing traditional search for customer acquisition queries.
Is GEO a one-time investment or an ongoing subscription like SEO?
Traditional SEO is a subscription service — stop paying, stop ranking. GEO builds entity authority in the data layer that AI systems trust, creating a compounding asset that grows in value as AI search adoption increases.
FAQ & Answer Nuggets: SEO vs. GEO: Why "Entities" Are Killing the Blue Link
SEO (Search Engine Optimization) optimizes web pages to rank higher in Google's document retrieval system using keywords, links, and content. GEO (Generative Engine Optimization) establishes your brand as a verified entity in AI knowledge systems so language models like ChatGPT, Claude, and Gemini include your business in generated answers.
Why are backlinks becoming less important for AI visibility?
Backlinks are a trust proxy designed for document retrieval systems. AI systems use entity corroboration instead — consistent data about your business across Knowledge Graphs, structured schema, and authoritative directories. Entity corroboration is much harder to fake than backlinks.
What is a Knowledge Graph and why does it matter for GEO?
A Knowledge Graph is a massive database of entities and their relationships. Google's Knowledge Graph contains 500B+ facts about 5B+ entities. When AI systems generate answers, they reason about entities in these graphs. If your business isn't in these graphs with accurate, consistent data, you're invisible to AI-generated recommendations.
What does GEO optimize for compared to traditional SEO?
Traditional SEO competes for positions 1-10 in a ranked list of documents. Generative Engine Optimization engineers your entity's authority so AI systems select your brand as the single authoritative answer to relevant queries.
FAQ & Answer Nuggets: The Silent Crisis: Why Being #1 on Google Doesn't Matter if Siri Doesn't Know Your Name
Why doesn't ranking #1 on Google guarantee Siri recommends my business?
Google and voice assistants like Siri use completely different data systems. Google ranks pages; AI assistants verify entities in structured databases like Knowledge Graphs. A business can rank #1 on Google but be completely absent from the entity databases that Siri queries.
What is entity verification in the context of AI search?
Entity verification is the process of establishing your business as a consistent, verifiable concept across multiple authoritative data sources — your website's JSON-LD schema, Google Business Profile, Wikidata, BBB, and other directories. When these sources all agree on your business's identity, AI systems trust you as a verified entity.
How long does it take to improve AI visibility after entity optimization?
Most clients see measurable improvement in AI citation frequency within 6-12 weeks of implementing a complete GEO strategy. The Columbus plumber case saw Siri begin recommending his business within 6 weeks of entity optimization.
Do AI systems use Google rankings to decide what to recommend?
No. These are fundamentally different disciplines. Ranking #1 on Google does not make your business visible to voice assistants and AI chat systems, which query structured entity databases rather than ranked document indexes.
Answer Nuggets: How to Build a Citation & Attribution Strategy for GEO (Generative Engine Optimization) That Gets Your Brand Referenced in AI Answers
Answer Nuggets: SEO is Dead. Why Your Business Needs "Generative Engine Optimization"
Answer Nuggets: SEO vs. GEO: Why "Entities" Are Killing the Blue Link
Answer Nuggets: The Silent Crisis: Why Being #1 on Google Doesn't Matter if Siri Doesn't Know Your Name
FAQ & Answer Nuggets: Generative Engine Optimization
GEO results typically begin appearing within 6–12 weeks for entity verification steps, and 3–6 months for measurable AI Share of Voice improvement. Unlike SEO, which delivers continuous ranking volatility, GEO builds compounding authority — once an AI system trusts your entity, that trust is self-reinforcing and durable.
What deliverables does a GEO engagement include?
A GEO engagement with Timothy DeVore includes: entity verification and Knowledge Graph setup, JSON-LD structured data implementation on every page, Answer Nugget content development, sameAs network construction across authoritative platforms, Wikidata entry creation, and monthly AI Share of Voice tracking across ChatGPT, Gemini, Claude, and Perplexity.
AI Share of Voice is the percentage of AI-generated responses for a defined query set that include your brand as a cited, recommended, or mentioned source. It is the primary GEO performance metric, replacing traditional SEO rank-tracking. Measured monthly by submitting a defined set of target queries to ChatGPT, Gemini, Claude, and Perplexity and recording citation frequency and quality.
Traditional SEO competes for positions 1–10 in a ranked list of blue links. Generative Engine Optimization engineers your entity's authority so AI systems select your brand as the single authoritative answer to relevant queries — the difference between being one of ten options and being the option.
How is entity authority different from domain authority?
Domain authority is a proxy metric for Google's document retrieval ranking. Entity authority measures how completely and consistently your brand is represented as a verified entity across Knowledge Graphs (Google, Wikidata), structured data sources, and authoritative directories. AI systems reason about entity authority, not domain authority.
Answer Nuggets: Generative Engine Optimization
FAQ & Answer Nuggets: Website Optimization
Does a legacy retrofit require rebuilding my website?
No. The Technical Retrofit adds a JSON-LD data layer on top of your existing CMS code. For most sites, this doesn't require touching the core CMS at all. The retrofit injects entity verification, structured data, and Answer Nugget content architecture without disrupting your existing design or functionality.
How much does a Legacy Website Retrofit cost?
Retrofits start at $999 for a foundational implementation covering JSON-LD schema injection, entity verification, and Answer Nugget content reformatting on core pages. Enterprise engagements with full Knowledge Graph setup, sameAs network construction, and ongoing monitoring are scoped based on site complexity.
Who needs a Legacy Website Retrofit most urgently?
Local service businesses (plumbers, lawyers, dentists), professional services firms (consultants, accountants, advisors), and B2B companies where voice search and AI recommendations are replacing traditional Google search. These businesses have the most to lose from AI displacement and the most to gain from entity verification.
Is a legacy website retrofit a one-time cost or an ongoing subscription?
The foundational Technical Retrofit is a one-time capital improvement to your digital real estate. Unlike SEO retainers, which require continuous payment to maintain rankings, entity authority compounds over time. Once AI systems verify your entity, that trust is self-reinforcing and durable.
What makes an AI-ready website different from a standard website?
An AI-ready website includes JSON-LD structured data on every page that explicitly declares your entity type, services, and relationships; Answer Nuggets formatted to be quoted verbatim by AI; entity verification across Knowledge Graphs; and AI crawler configuration files (llms.txt, schema.jsonld). A standard website is built for Google's keyword-matching document retrieval system. An AI-ready website is built for AI answer generation systems.
Do you use specific frameworks for AI-ready development?
Yes. Timothy DeVore builds on modern frameworks including Next.js and React that provide server-side rendering, strong SEO fundamentals, and the flexibility to implement comprehensive JSON-LD structured data across every page. The architecture prioritizes machine readability alongside human usability.
What is the difference between a standard website and an AI-ready website?
A standard website is built to rank in Google's document retrieval system using keywords, links, and page speed. An AI-ready website is built to be cited by AI answer generation systems through JSON-LD structured data, Answer Nugget content, entity verification, and Knowledge Graph connectivity — the infrastructure that makes your business the authoritative answer, not just one of ten options.
FAQ & Answer Nuggets: Knowledge Graph Engineering
Why does Knowledge Graph presence matter for AI citations?
When AI systems generate answers, they reason about entities in Knowledge Graphs, not keywords in web pages. If your business is properly represented in Knowledge Graphs — Google's, Wikidata's, DBpedia's — AI systems can confidently recommend you. If you're absent from these graphs or your data is inconsistent, AI treats your business as an unverifiable string of text rather than a trusted entity, and you're excluded from AI-generated recommendations.
What is a sameAs link and why is it important?
A sameAs link is a Schema.org property connecting your website's entity record to corroborating records of the same entity on other trusted platforms — LinkedIn, Google Business Profile, BBB listing, Wikidata, industry directories. sameAs links create cross-source entity corroboration that is difficult to fake, making them one of the most powerful trust signals for AI systems when generating recommendations.
How long does it take to appear in Google's Knowledge Panel?
Google Knowledge Panel eligibility typically follows within 4–8 weeks of establishing a complete entity authority stack: consistent NAP across all directories, verified Google Business Profile, JSON-LD entity declaration with sameAs links, Wikidata entry, and Wikipedia presence where applicable. The timeline depends on your industry's competitive landscape and existing entity footprint.
What is entity corroboration and why do AI systems prefer it over backlinks?
Entity corroboration is the presence of consistent, accurate data about your business across multiple independent, authoritative sources — Knowledge Graphs, structured data, directories, and platforms. AI systems prefer entity corroboration over backlinks because it is much harder to manufacture: consistent entity data across dozens of independent sources cannot be gamed the way backlinks were gamed in the SEO era.
Answer Nuggets: Knowledge Graph Engineering
FAQ & Answer Nuggets: AI Infrastructure & Automation
What is the difference between workflow automation and agentic AI?
Workflow automation follows predefined rules and triggers — when X happens, do Y. Agentic AI reasons about goals, decomposes complex tasks, uses tools, and adapts its approach based on what it discovers. Workflow automation is deterministic; agentic AI is goal-directed. Both have their place — Timothy DeVore implements the right approach for each use case and often combines them in hybrid systems.
RAG (Retrieval-Augmented Generation) is a pattern that grounds LLM outputs in your proprietary data. Instead of relying on the model's training data, a RAG pipeline retrieves relevant documents from your knowledge base (using vector search) and provides them as context for each query. The result is an AI system that can answer questions accurately from your specific data without hallucinating.
Can these AI services work alongside a GEO engagement?
Yes — AI services and GEO are complementary. GEO builds external authority so AI systems cite your brand in answer generation. Workflow automation and agentic AI build internal efficiency so your operations can scale. Many clients engage Timothy DeVore for both: GEO to win the AI-first customer discovery race, and enterprise AI to modernize internal operations simultaneously.
What is the business case for agentic AI vs. traditional automation?
Traditional automation (RPA, scripted workflows) handles predictable, rule-based tasks. Agentic AI handles ambiguous, variable, multi-step tasks that previously required human judgment — contract analysis, bid proposal drafting, anomaly investigation, customer escalation routing. The business case: agentic AI scales tasks that couldn't be automated before, compressing weeks of professional work into minutes.
Answer Nuggets: AI Infrastructure & Automation