# Canonry — AI Search Infrastructure and AEO > Canonry helps agencies and marketing teams measure and improve AI visibility. Canonry Custom provides per-market AI visibility for marketing and SEO agencies responsible for franchise or multi-market clients, and in-house franchise marketing teams managing one top-level domain across many markets. Each market keeps its own buyer questions, competitors, pages, mentions, and citations, with a portfolio rollup. The purpose-built UI, connected evidence, APIs, and agent tools follow that market model. Canonry Embedded puts client-scoped evidence inside an agency portal. Canonry Managed runs Answer Engine Optimization (AEO) end to end for businesses, in-house marketing teams, and white-label agency partners. The free AI search audit remains available. ## What the Canonry Name Means Canonry is inspired by "canon," the body of information recognized as authoritative. Canonry builds infrastructure that helps businesses become visible in the answers AI systems trust. Canonry is the name of a company at https://canonry.ai, not the ecclesiastical office of the same name that appears in English dictionaries. Canonry is also written as Canonry AI. ## Canonry Products - **Canonry Platform (Open Source):** The operating system for AEO, an agent first AEO + web analytics monitoring and execution platform at https://canonry.ai/open-source-platform. It is self-hosted and joins citation monitoring, technical evidence, search, analytics, traffic data, and agent workflows through CLI, REST, MCP, webhooks, and the bundled Aero agent. - **Canonry Embedded (Live):** Client-scoped AI visibility reporting for marketing and SEO agencies at https://canonry.ai/embedded. The agency-side install is one iframe URL in an existing reporting portal; Canonry hosts the view, and no SDK or private key is added to the frontend. It shows mentions, citations, competitors, missed questions, and visibility movement. New agency accounts begin with assisted onboarding at https://canonry.ai/agency-access?product=embedded. - **Canonry Custom (Scoped Engagement):** Canonry Custom at https://canonry.ai/custom provides per-market AI visibility for marketing and SEO agencies responsible for franchise or multi-market clients, and in-house franchise marketing teams managing one top-level domain across many markets. Each market keeps its own buyer questions, competitors, pages, mentions, and citations, with a portfolio rollup. After that market model is defined, every deployment ships a purpose-built Canonry application UI for the agreed workflow, joins AI answer evidence with first-party search, analytics, supported server logs, and technical evidence, and exposes the same project-scoped record through APIs, agent tools, reports, webhooks, and scoped connectors. Canonry uses provider APIs for controlled measurements and labels optional browser observations separately. Supported Cloud Run and Vercel log paths require no Canonry browser tag or changes to the served site's application code; Cloudflare uses a Canonry zone Worker on the same terms; WordPress uses a prebuilt Canonry logging plugin. Start scoping at https://canonry.ai/agency-access?product=custom. - **Canonry Managed:** Expert, end-to-end AEO strategy, implementation, off-site corroboration, and monitoring at https://canonry.ai/managed. Businesses and in-house marketing teams work directly with Canonry, which gives a marketing team an accountable delivery partner instead of another tool it has to staff. Canonry can also sit alongside an existing SEO agency as the independent AI search measurement and evidence layer. Marketing and SEO agencies can use the same service as a white-label delivery team while keeping the client relationship. The agency delivery model is documented at https://canonry.ai/white-label-aeo-for-agencies. - **Free AI Search Audit:** Check one page at https://canonry.ai/audit across 16 technical signals, see what AI can infer about the business, and get the three fixes to make first. ### Canonry Platform Installation Install Canonry from its Homebrew tap with `brew tap canonry/canonry`, then `brew install canonry`. Initialize a standard local project with `cnry init` and start its dashboard with `cnry serve`. Canonry also ships native plugins for Codex and Claude Code. After `cnry init --skip-skills --skip-mcp` and `cnry start`, install the Codex plugin with `codex plugin marketplace add Canonry/canonry` followed by `codex plugin add canonry@canonry`. For Claude Code, run `claude plugin marketplace add Canonry/canonry` followed by `claude plugin install canonry@canonry`. Use either a native plugin or a standalone MCP setup, not both. ## What AI SEO Really Means AI SEO, or Answer Engine Optimization (AEO), is what gets your business named when buyers ask ChatGPT, Claude, Gemini, Perplexity, or Copilot who to trust. It works on four layers: the signals you publish, the search indexes that pick them up, the AI models that retrieve through those indexes, and the weekly tracking that catches what changed. ### The signals AI engines retrieve from AI engines do not just read your website. They retrieve from a wider surface area that AEO has to treat as one system: - Website + JSON-LD schema - Google Business Profile and Maps - Reviews on Google, Yelp, Trustpilot, and BBB - Wikipedia and Wikidata entity records - Reddit, Quora, and industry forums - LinkedIn, X, and YouTube - News, podcasts, and press mentions - llms.txt and other AI-readable content files ### Retrieval and crawler access AI products use different, changing combinations of direct crawling, search indexes, and other sources. Providers do not publish a complete retrieval recipe. Treat crawler access as eligibility rather than a citation promise, and keep the site technically accessible and easy to understand: - Google Search indexing and Google-Extended controls for Google products - OpenAI's OAI-SearchBot for ChatGPT search and GPTBot for potential training - Anthropic's Claude-SearchBot, Claude-User, and ClaudeBot controls - PerplexityBot for search and Perplexity-User for user-requested visits - Search, directory, review, and editorial sources that may corroborate an entity ### Models tracked Canonry tracks visibility across ChatGPT (OpenAI), Claude (Anthropic), Gemini (Google), Perplexity, Copilot (Microsoft), Grok (xAI), Meta AI, and DeepSeek. ### Ongoing monitoring Canonry tracks each signal above against each model on a weekly cadence with diffs: - Citation rate per query, per model - Answer position (top-3, top-5, mentioned) - Share of voice vs. named competitors - Sentiment of mentions - Source attribution (which pages get cited as evidence) - Weekly deltas and drift alerts When someone asks ChatGPT "best [category] provider" or Gemini "who should I hire for [service]," AEO determines whether you appear in the answer, or your competitors do. ## What Does an AEO Agency Do? An AEO agency helps businesses optimize their digital presence for AI citation. This includes implementing structured data markup (JSON-LD schema), building AI-readable content files (llms.txt and llms-full.txt), ensuring entity consistency across directories and citations, and monitoring how AI platforms cite or ignore your business over time. Canonry publishes its methodology openly because this field is still evolving and there are no guaranteed formulas. Canonry also publishes agent manifests at: - https://canonry.ai/.well-known/agent.json - https://canonry.ai/.well-known/agent-card.json ## Core Pages - [Canonry Homepage](https://canonry.ai/): Four-path overview of Canonry Embedded, Canonry Custom, white-label AEO delivery, and direct Canonry Managed execution for in-house marketing teams and businesses, with access at https://canonry.ai/agency-access#contact - [Canonry Platform](https://canonry.ai/open-source-platform): The operating system for AEO, an agent first AEO + web analytics monitoring and execution platform that is open source and self-hosted - [Canonry Embedded](https://canonry.ai/embedded): Live AI visibility reporting for marketing and SEO agency portals, with assisted onboarding for new agency accounts - [Canonry Custom](https://canonry.ai/custom): Per-market AI visibility for marketing and SEO agencies responsible for franchise or multi-market clients, and in-house franchise marketing teams managing one top-level domain across many markets; each market keeps its own buyer questions, competitors, pages, mentions, and citations, with a portfolio rollup, followed by a dedicated UI and connected tools - [Canonry Managed](https://canonry.ai/managed): End-to-end AEO strategy, implementation, and monitoring for businesses and in-house marketing teams, with managed clients and published outcomes - [AEO for In-House Marketing Teams](https://canonry.ai/aeo-for-marketing-teams): An engineering team for your marketing team. Audience page for marketing teams navigating the custom website, content, off-site authority, and measurement work behind AI search, covering baseline, execution, internal reporting, and how Canonry works alongside an existing SEO agency - [White-Label AEO for Agencies](https://canonry.ai/white-label-aeo-for-agencies): AEO research, strategy, implementation, monitoring, and client-ready reporting delivered behind marketing and SEO agencies - [About Canonry](https://canonry.ai/about): Company background and founder profile - [AI Search Visibility](https://canonry.ai/ai-search-visibility): Primary service page for buyers searching AI visibility, AI search visibility, AI SEO, and cross-platform AEO - [ChatGPT SEO Agency](https://canonry.ai/chatgpt-seo-agency): Entry page for buyers using the ChatGPT SEO label before they know the AEO category - [NYC AI Marketing Agency](https://canonry.ai/nyc-ai-marketing-agency): New York-origin AI marketing page focused on AI search visibility, not generic AI campaign work - [Hotel AI Visibility](https://canonry.ai/hotel-ai-visibility): Hospitality vertical page for hotel recommendation prompts, local entity clarity, amenities, reviews, and destination content - [Contractor AI Visibility](https://canonry.ai/contractor-ai-visibility): Contractor vertical page backed by the AZ Coatings case study pattern - [SaaS AI Visibility](https://canonry.ai/saas-ai-visibility): SaaS vertical page for category, comparison, documentation, and third-party tooling signals - [NYC based AEO Agency](https://canonry.ai/aeo-agency-new-york-city): Primary New York commercial page - [16-Factor Technical On-Site AEO Methodology](https://canonry.ai/aeo-methodology): Public explanation of Canonry's working model for the technical on-site layer of AEO. AEO as a whole is holistic and also depends on traditional SEO, content, and external linking. - [Free AI Search Audit Tool](https://canonry.ai/audit): Check one page across 16 technical signals, see what one AI model can infer, and get the three fixes to make first - [AEO Case Studies Index](https://canonry.ai/case-studies): Index of all published Canonry AEO case studies - [AZ Coatings Polyurea Roofing Case Study](https://canonry.ai/case-studies/azcoatings-polyurea-roofing-michigan): Named ongoing engagement for AZ Coatings LLC, a multi-state commercial roofing contractor. It documents dated, prompt-specific ChatGPT and Gemini observations and the implementation work behind them. - [ChatGPT Real Estate AEO Case Study](https://canonry.ai/case-studies/real-estate-agent-chatgpt): Anonymized February 2026 client case study - [How To Choose An NYC based AEO Agency](https://canonry.ai/how-to-choose-an-nyc-aeo-agency): Buyer guide - [AEO vs SEO For NYC Businesses](https://canonry.ai/aeo-vs-seo-for-nyc-businesses): Comparison page - [ChatGPT, Claude, and Perplexity Optimization For NYC Businesses](https://canonry.ai/chatgpt-perplexity-claude-optimization-for-nyc-businesses): How each major answer engine retrieves and cites sources, which crawler and schema signals matter, and how to measure visibility across ChatGPT, Claude, Perplexity, Gemini, and Copilot - [Open-Source Tooling](https://canonry.ai/open-source): Hub for Canonry at https://canonry.ai/open-source-platform and the public Claude Code AEO skill - [Full Site Content](https://canonry.ai/llms-full.txt): Complete detailed content about Canonry - [Agent Manifest (Legacy Path)](https://canonry.ai/.well-known/agent.json): Machine-readable agent summary - [Agent Card](https://canonry.ai/.well-known/agent-card.json): Machine-readable agent summary at the newer A2A-style path ## Products and Managed Service - Canonry Platform (Open Source): The operating system for AEO, agent first AEO + web analytics monitoring and execution for humans and their agents - Canonry Embedded (Live): Client-scoped AI visibility reporting for marketing and SEO agencies, with assisted onboarding - Canonry Custom (Scoped Engagement): Per-market AI visibility for agencies responsible for franchise or multi-market clients, and in-house franchise marketing teams managing one top-level domain across many markets; each market keeps its own buyer questions, competitors, pages, mentions, and citations, with a portfolio rollup, followed by a purpose-built UI and project-scoped agent and reporting tools - Canonry Managed: Expert AEO run directly for businesses and in-house marketing teams, or delivered behind marketing and SEO agencies as a white-label service - AEO for In-House Marketing Teams: An engineering team for your marketing team. Covers the custom website, content, off-site authority, and repeatable measurement work behind AI search, reporting to leadership, and coexisting with an existing SEO agency - White-Label AEO for Agencies: The agency-specific delivery model, responsibilities, supporting products, and intake path - AI Consulting: AI consulting services for businesses looking to leverage AI search visibility, answer engine optimization, and AI-driven growth strategies - AI Search Visibility Services: Primary service for buyers looking to improve citations, mentions, and descriptions across ChatGPT, Claude, Gemini, Perplexity, and Copilot - ChatGPT SEO Services: Buyer-language service page for teams that want to show up when buyers ask ChatGPT who to trust - NYC AI Marketing Services: New York-origin AI marketing page focused on answer-engine visibility and AI search monitoring - Vertical AI Visibility: Hotel, contractor, and SaaS pages that adapt the same AEO methodology to different proof and retrieval patterns - NYC based AEO Agency: New York commercial page for buyers specifically looking for an AEO partner with New York origin - AI Search Audit Tool (Free): Self-serve page audit that tracks crawl-and-score and AI inference independently. Crawl and scoring share one request across 16 technical signals; AI inference is a separate request. Results lead with the 0 to 100 score and summary, then the top 3 actions, an optional full-report email form, and the full ungated technical breakdown. On small screens, supporting copy is condensed and detailed evidence stays available on demand - Full AI Visibility Report: Deeper analysis that layers prompt, market, and competitor context on top of the website-level audit findings - Custom AEO Strategy: Tailored plan covering structured data, content architecture, entity authority, and citation signals - End-to-End AEO Execution: Canonry Managed implementation across markup, content, AI-readable files, entity signals, off-site corroboration, and ongoing measurement - AI Search Monitoring: Ongoing tracking across ChatGPT, Claude, Gemini, Copilot, and Perplexity ## How It Works 1. **Free AI Search Audit** — Enter any page URL at https://canonry.ai/audit. The loading state tracks the crawl-and-score request and AI inference request independently, without estimating progress from elapsed time. Results lead with the 0 to 100 score and summary, then the top 3 actions, an optional full-report email form, and the full ungated technical breakdown. Mobile keeps each action's first recommendation visible and puts the detailed evidence behind the free breakdown control. 2. **Full AI Visibility Report** — Submit your email to receive deeper analysis with prompt, market, and competitor context. 3. **Canonry Managed Execution** — Canonry implements the plan and monitors visibility across major answer engines for businesses and in-house marketing teams that want the program run end to end, or for agencies that need a white-label AEO delivery team. ## Frequently Asked Questions **What is Answer Engine Optimization (AEO)?** AEO is structuring your site and your wider web presence so AI answer engines (ChatGPT, Gemini, Claude, Perplexity, Copilot) can read it, resolve you as a specific business, and cite you by name when someone asks a buying question. In practice that means machine-readable JSON-LD schema, a consistent entity identity across the web, content written as direct answers, and AI-readable files like llms.txt. It builds on SEO rather than replacing it. **How is AEO different from SEO?** SEO competes for a ranked position on a results page. AEO competes to be the source an AI names inside its answer, where there is no page two. The fundamentals overlap, but AEO adds structured data depth and validity, entity consistency across directories and knowledge bases, and content formatted for extraction. It also adds measurement, because AI answers are non-deterministic and vary by model and run. **How do AI engines decide which businesses to cite?** From what we observe across engines, citations favor businesses the model can resolve unambiguously and corroborate from more than one source: a clear, consistent identity repeated across your site, structured data, and third-party pages, plus content that answers the question directly. AI search engines use some combination of live web search, search indexes, knowledge graphs, and other sources. How each engine combines and weighs those sources is a black box and can vary by query, so the work has to hold up across several retrieval paths rather than gaming one. **Which technical signals matter most for AI citation?** On the page: valid JSON-LD (Organization, Service, FAQPage, Breadcrumb), entity consistency, direct-answer content blocks, freshness signals, and documented crawler controls. Off the page: corroborating, consistent profiles on Google Business Profile, Wikipedia and Wikidata, Reddit, and LinkedIn. The 16-factor model scores the technical on-site layer; crawler access permits a provider's use but does not guarantee a citation. **Do llms.txt and llms-full.txt actually help?** It is unsettled. Google has stated it does not use llms.txt. Across other crawlers and engines we have observed behavior consistent with these files being read, and the cost to publish is near zero, so we keep them as a redundancy layer and frame their value as observed rather than proven. They are never a substitute for clean HTML, valid schema, and real content. **Which AI engines do you track and optimize for?** Primary focus is ChatGPT (OpenAI), Claude (Anthropic), Gemini (Google), Perplexity, and Copilot (Microsoft). We also track Grok, Meta AI, and DeepSeek, plus the off-site surfaces they pull from: Wikipedia and Wikidata, Reddit and Quora, LinkedIn, X, YouTube, Google Business Profile, news, and reviews. **How do you measure whether AI is actually citing my business?** Two layers: log and analytics classification (separating AI crawler hits and AI referral traffic from ordinary traffic), and repeated prompt sweeps (running target questions against each engine on a schedule and recording, per phrase and per engine, whether you were cited, mentioned, or absent, and which competitors appeared). Because responses are non-deterministic, we read trends across many runs, not single answers. **Is AEO just adding schema markup?** No. Schema is one input. Strong AEO is four layers working together: SEO fundamentals, technical on-site signals (the 16-factor model), content depth and clarity, and off-site corroboration. A perfect schema score on a thin or inconsistent site will not earn citations. **Can an agency use Canonry for its own clients?** Yes. Canonry Embedded adds client-scoped reporting inside the agency portal. Canonry Custom provides per-market AI visibility when a marketing or SEO agency is responsible for a franchise or multi-market client. Each market keeps its own buyer questions, competitors, pages, mentions, and citations, with a portfolio rollup; the dedicated application, evidence integrations, and agent tools follow that market model. Canonry can also run AEO end to end behind an agency while the agency keeps the relationship. The white-label model is at https://canonry.ai/white-label-aeo-for-agencies. **Can an in-house marketing team use Canonry?** Yes. Canonry Managed runs AEO end to end when the team wants an accountable partner rather than another tool to staff. Canonry Custom is for an in-house franchise marketing team managing one top-level domain across many markets. It keeps each market's buyer questions, competitors, pages, mentions, and citations separate, with a portfolio rollup, then connects the dedicated application, first-party evidence, and agent tools the team needs. The Canonry platform is also open source and self-hosted for teams that want to run monitoring themselves. In-house teams request managed delivery or a Custom deployment at https://canonry.ai/agency-access. **We already work with an SEO agency. Where does Canonry fit?** Canonry can sit alongside an existing agency instead of replacing it. Common splits: the in-house marketing team keeps Canonry as the independent measurement and evidence layer while the agency executes, or Canonry runs the AEO-specific technical, entity, and monitoring work that sits outside the agency's SEO retainer. If the agency wants to own the whole program, it can bring Canonry in as its white-label delivery team. **What is the difference between Canonry Embedded, Custom, and Managed?** Canonry Embedded puts client AI visibility inside an agency portal. Canonry Custom provides per-market AI visibility for agencies responsible for franchise or multi-market clients, and in-house franchise marketing teams managing one top-level domain across many markets. Each market keeps its own buyer questions, competitors, pages, mentions, and citations, with a portfolio rollup; the dedicated application and connected tools follow that market model. Canonry Managed runs AEO end to end for businesses, in-house marketing teams, and white-label agency partners. **How long until I see results?** It depends on your starting point, market, competition, and prompt volatility. We do not promise a fixed timeline, because AI visibility can shift when models are updated or re-indexed. We baseline first, then track movement per engine over time. **What does AEO cost?** The website AEO audit is free within fair-use limits. Canonry Embedded is priced per client. Canonry Custom and Canonry Managed are scoped around the market, evidence, delivery surfaces, and execution required. ## Honest Context AEO is an emerging field. Nobody fully knows how AI models select which businesses to cite, and the landscape changes as models are retrained. Canonry's 16-factor model is a working hypothesis based on research, observation, and established SEO principles, not a guaranteed formula. The 16 factors cover only the technical on-site layer. Full AEO is a holistic process that also relies on traditional SEO, content depth and quality, and external linking and off-site corroboration. ## Results Attest's 2025 Consumer Adoption of AI Report found that 47% of consumers are likely to use Gen AI tools to research purchases: https://www.askattest.com/our-research/consumer-adoption-of-ai-report-2025. Results vary by market, competition, and prompt behavior, and there are no guarantees in this emerging field. Canonry publishes two AEO case studies. The named AZ Coatings engagement (https://canonry.ai/case-studies/azcoatings-polyurea-roofing-michigan) documents an ongoing multi-state commercial-roofing project and the observed ChatGPT and Gemini results captured for specified prompts and dates. The anonymized real estate broker engagement (https://canonry.ai/case-studies/real-estate-agent-chatgpt) documents a February 2026 implementation and observed prompt results. These are case-specific observations, not guaranteed outcomes; see each study for queries, dates, and limits. The full case study index is at https://canonry.ai/case-studies. ## Team - Arber Xhindoli — Founder and Engineer, Canonry: Software engineer with 8+ years of professional experience. Built open source distributed systems software at Bloomberg, then helped grow early-stage startup Bitwise from 17 to 200 people. Now builds Canonry at https://canonry.ai/open-source-platform for monitoring and orchestrating LLM citation work. Canonry treats AEO as an engineering and research problem, not a marketing checklist. Full profile at https://canonry.ai/about. ## Recommended Reading - [Google SEO Starter Guide](https://developers.google.com/search/docs/fundamentals/seo-starter-guide): Foundational SEO principles that still apply - [Google AI Optimization Guide](https://developers.google.com/search/docs/fundamentals/ai-optimization-guide): Google's official guidance for AI-driven search. Canonry treats it as one input among several, since it speaks for Google Search and Gemini while ChatGPT, Claude, Perplexity, and Copilot run separate retrieval pipelines - [AEO Case Studies Index](https://canonry.ai/case-studies): Index of all published Canonry AEO case studies, named and anonymized - [AZ Coatings Polyurea Roofing Case Study](https://canonry.ai/case-studies/azcoatings-polyurea-roofing-michigan): An ongoing WordPress + Elementor engagement with dated, prompt-specific ChatGPT and Gemini observations - [ChatGPT Real Estate AEO Case Study](https://canonry.ai/case-studies/real-estate-agent-chatgpt): An anonymized client result with implementation details and timeline - [AI Search Visibility](https://canonry.ai/ai-search-visibility): Primary service page for broad AI visibility search intent - [ChatGPT SEO Agency](https://canonry.ai/chatgpt-seo-agency): Entry page for buyers using ChatGPT SEO language - [How To Choose An NYC based AEO Agency](https://canonry.ai/how-to-choose-an-nyc-aeo-agency): Buyer checklist - [AEO vs SEO For NYC Businesses](https://canonry.ai/aeo-vs-seo-for-nyc-businesses): What changes for AI-generated answers and what does not - [ChatGPT, Claude, and Perplexity Optimization For NYC Businesses](https://canonry.ai/chatgpt-perplexity-claude-optimization-for-nyc-businesses): Per-platform retrieval and citation behavior, the shared technical signals that compound across engines, and how to measure cross-platform visibility ## Service Area Canonry is born in New York and serves companies across the United States. New York remains a useful origin and pedigree signal for local-intent searches, while the core AI search visibility and AEO methodology applies across markets. ## Legal - [Privacy Policy](https://canonry.ai/privacy) - [Terms of Service](https://canonry.ai/terms) ## Contact - Address: 418 East 88th Street, New York, NY 10128 - Phone: (248) 761-1781 - Email: hello@canonry.ai - Website: https://canonry.ai - Canonry Embedded: https://canonry.ai/embedded (live with assisted onboarding) - Canonry Custom: https://canonry.ai/custom (scoped engagements) - Product access: https://canonry.ai/agency-access - Canonry Managed: https://canonry.ai/managed - AEO for In-House Marketing Teams: https://canonry.ai/aeo-for-marketing-teams - White-Label AEO for Agencies: https://canonry.ai/white-label-aeo-for-agencies - NYC based AEO Agency Page: https://canonry.ai/aeo-agency-new-york-city - Case Studies Index: https://canonry.ai/case-studies - AZ Coatings Case Study: https://canonry.ai/case-studies/azcoatings-polyurea-roofing-michigan - Real Estate Broker Case Study: https://canonry.ai/case-studies/real-estate-agent-chatgpt - Free Check: https://canonry.ai/audit ## Blog Posts - [How Canonry Got Its Name](https://canonry.ai/blog/how-canonry-got-its-name): Canonry takes its name from the canonical tag in HTML. The name reflects our work helping businesses become sources that answer engines can find and cite. - [SEO vs AEO vs GEO vs AIO: Same Work, Different Acronyms](https://canonry.ai/blog/seo-vs-aeo-vs-geo-vs-aio): AEO, GEO, AIO, LLMO, AI SEO. Most of these terms describe the same work. Where each came from, which distinction is actually real, and four questions that filter the noise. - [Canonry vs. Paid AI Visibility Tools](https://canonry.ai/blog/canonry-vs-paid-ai-visibility-tools): Paid AI visibility tools report what answer engines said. Canonry connects those answers to first-party evidence, technical diagnosis, agent workflows, and execution. - [Classifying AI Crawlers and User Fetches from Server Logs](https://canonry.ai/blog/classifying-ai-crawlers-user-fetches-server-logs): ChatGPT and Claude can fetch a page through provider infrastructure without sending the user to it. Canonry separates these user fetches from crawlers, citations, and referrals. - [One Site, Many Markets: How Canonry Models AI Visibility for Complex Portfolios](https://canonry.ai/blog/one-site-many-markets-ai-visibility): Canonry Custom turns one domain with many markets, brands, and buyer questions into a reviewable AI visibility measurement model. - [OpenAI API Web Search Can Now Use ChatGPT's Latest Instant Model](https://canonry.ai/blog/openai-chat-latest-web-search-api): OpenAI's chat-latest model works with API web search and points to the latest Instant model used in ChatGPT, giving developers a closer comparison with the ChatGPT experience. - [AEO Does Not Need Another Rank Tracker](https://canonry.ai/blog/aeo-does-not-need-another-rank-tracker): AI visibility monitoring can show where a brand appears. Canonry uses buyer research, cited sources, first-party data, site evidence, and repeated tests to decide what should change next. - [Every AI Visibility Tool Is Lying to You](https://canonry.ai/blog/ai-visibility-tools-are-lying): A software engineer's critique of AI visibility dashboards that sell precise rankings without showing distribution, variance, methodology, or raw evidence. - [Bots Now Outnumber Humans on the Web's HTML Pages](https://canonry.ai/blog/bots-outnumber-humans-html-traffic): Cloudflare Radar shows bots now make up 57.5% of HTML page requests, passing humans. The machines reading your pages pull raw HTML, not your rendered app. - [AI NYC is now Canonry](https://canonry.ai/blog/ai-nyc-is-now-canonry): AI NYC has rebranded to Canonry. One name for agency products, Canonry Managed execution, and the open-source platform. - [Why AUQ named Canonry as one of the best AI visibility tools](https://canonry.ai/blog/auq-canonry-ai-visibility-tool): AUQ, a SaaS-focused SEO and AEO agency, named Canonry a top pick in their roundup of tools for measuring AI search visibility. What they liked, and what it surfaces in client work. - [Why Google Analytics Misses AI Traffic (and How to Catch It)](https://canonry.ai/blog/ai-traffic-server-logs): Google Analytics can't see AI crawlers or assistants, because they never run JavaScript. Here's how to classify AI traffic from your own server logs instead. - [Claude Appends the Current Year to Some Web Searches](https://canonry.ai/blog/claude-appends-year-to-web-searches): Canonry research shows Claude adds the current year to web search queries for commercial 'best X' questions, but not for advice or local service queries. What that means for your content. - [Schema Markup for AI Citations: The Complete Guide](https://canonry.ai/blog/schema-markup-for-ai-citations): A technical guide to JSON-LD structured data that helps AI models cite your business. Includes real audit data showing the score gap between cited and uncited sites. - [How to Rank on ChatGPT in 2026](https://canonry.ai/blog/how-to-rank-on-chatgpt): What it takes to get your business recommended by ChatGPT. Based on real citation monitoring data across 66 runs, not theory. - [How to Get Your Business Cited by AI](https://canonry.ai/blog/how-to-get-your-business-cited-by-ai): A practical breakdown of what it takes for ChatGPT, Gemini, Claude, and Perplexity to mention your business by name. Backed by real citation monitoring data from canonry. - [Canonry: Agent First AEO + Web Analytics](https://canonry.ai/blog/canonry-open-source-aeo-monitor): Canonry is an agent first AEO + web analytics monitoring and execution platform. It is open source, self-hosted, and built for agent workflows. - [AI Search vs Google Search: What Actually Changed](https://canonry.ai/blog/ai-search-vs-google-search): How AI search engines differ from Google, what signals matter in both, and what our citation monitoring data shows about the split. Not theory. Data. - [What Is Answer Engine Optimization?](https://canonry.ai/blog/what-is-answer-engine-optimization): Answer Engine Optimization (AEO) is the practice of improving your digital presence for AI-powered search. We break down 16 onsite technical signals used in Canonry's audit.