AI search infrastructure for agencies

Turn AI search into work clients can see.

Canonry gives marketing and SEO agencies the evidence, client reporting, and next-spend decisions to build a serious AI search offering without building the infrastructure themselves.

Explore agency productsSee Canonry Embedded
Canonry AdsPrivate beta
Canonry EmbeddedLive · Assisted onboarding

Canonry products and managed services

  1. For agencies

    Canonry Embedded

    Put AI visibility inside your client portal.
    Client reporting product

    Paste one iframe URL into your portal. Canonry hosts the client-scoped view; no SDK or private key is added to your frontend.

    Live · Assisted onboarding
    Explore Canonry EmbeddedRequest assisted onboarding
  2. For agencies + advertisers

    Canonry Ads

    Find gaps that may merit a ChatGPT Ads test.
    Paid-test decision product

    Find the queries buyers use to discover your clients’ brands. Target paid ads where those brands do not appear.

    Private beta
    Explore Canonry AdsRequest beta access
  3. For businesses

    Canonry Managed

    Start with a free AEO technical audit.
    Free AEO baseline

    Check one public URL across 16 onsite signals, see what one live Gemini model can infer, and get three prioritized fixes.

    Free · No email required
    Run the free audit
Live · Assisted onboarding

Canonry Embedded

AI visibility in your client portal.

Paste one iframe URL into your existing portal. Canonry hosts the client-scoped view, with no SDK, private key, or second client login.

Explore Canonry EmbeddedRequest assisted onboarding
Private beta

Canonry Ads

Find gaps that may merit a ChatGPT Ads test.

Find the queries buyers use to discover your clients’ brands. Target paid ads where those brands do not appear.

Explore Canonry AdsRequest beta access

AI Search Is Where SEO and SEM Converge

SEO builds the evidence AI systems can retrieve and cite. SEM captures live demand and, where paid inventory exists, puts a sponsored next step beside the answer.

AI Search brings both into one buyer journey, measured against the same questions, competitors, citations, paid coverage, and conversions.

An AI Search diagram showing SEO and SEM as separate visibility lanes. Search indexes and AI models synthesize the available evidence into earned citations and sponsored next steps where supported. One measurement layer tracks citations, paid coverage, question gaps, competitors, and conversions.
SEO · Earned Visibility

Build the evidence

  • Useful content + JSON-LD schema
  • Authority, links + reviews
  • Local + entity signals
  • Technical crawl + index health
SEM · Paid Visibility

Capture live demand

  • High-intent search terms
  • Search + Shopping campaigns
  • Landing page + offer testing
  • Click + conversion data
AI Search

Retrieve, reason, rank

  • Search indexes + live web
  • AI models + retrieval
  • Sources, entities + reviews
  • Paid inventory, where supported
The Answer Surface
“Best [your service] for my business?”
EarnedYour business is cited
PaidA sponsored next step, where supported

One Measurement Layer

We track earned citations and paid presence against the same questions, competitors, and conversion paths, weekly, with diffs.

  • Citation ratePer query, per model.
  • Paid coverageWhere sponsored inventory exists.
  • Query gapsHigh-intent questions you miss.
  • Share of voiceEarned and paid presence.
  • Source attributionPages and domains behind answers.
  • ConversionsWhat turns visibility into action.
Read the 16-factor onsite technical methodologyExplore AI search visibilityReview published case studies

Direct answers

Frequently asked questions about AI search visibility.

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 (crawlable, fast, credible pages), but AEO adds three layers SEO does not prioritize: structured data depth and validity, entity consistency across directories and knowledge bases, and content formatted for extraction such as definitions, FAQs, and tables. 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. That means a clear, consistent identity (name, location, services) repeated across your site, your structured data, and third-party pages, plus content that answers the specific question directly. Each engine retrieves differently, some through live web search, some through a search index, some through a knowledge graph, so the work has to hold up across several systems rather than gaming one. We treat the exact weighting as observed, not confirmed.

Which technical signals matter most for AI citation?

On the page: valid JSON-LD (Organization, Service, FAQPage, Breadcrumb), entity consistency (matching name and sameAs links everywhere you appear), direct-answer content blocks, freshness signals, and AI-crawler access in robots.txt for GPTBot, ClaudeBot, PerplexityBot, and Google-Extended. Off the page: corroborating, consistent profiles on the sources engines retrieve from, including Google Business Profile, Wikipedia and Wikidata, Reddit, and LinkedIn. The on-site layer is the part you fully control, and it is what our 16-factor model scores.

Do llms.txt and llms-full.txt actually help?

It is unsettled, and we say so. 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 them 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 these engines pull from: Wikipedia and Wikidata, Reddit and Quora, LinkedIn, X, YouTube, Google Business Profile, news, and reviews. Because each behaves differently, we optimize for signals that hold across engines rather than one vendor playbook.

How do you measure whether AI is actually citing my business?

Two layers. First, log and analytics classification: separating AI crawler hits (GPTBot, ClaudeBot, and peers) and AI referral traffic from ordinary traffic. Second, repeated prompt sweeps: running your 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 puts client-scoped AI visibility reporting inside the portal an agency already runs. Canonry Ads adds private-beta decision support for paid tests. Canonry Managed can also run AEO delivery end to end behind the agency as a white-label service while the agency keeps the client relationship.

How do Canonry Embedded and Canonry Ads work together?

Canonry Embedded makes AI visibility evidence client-visible inside the agency portal. Canonry Ads helps an agency or individual advertiser decide which ChatGPT Ads tests are worth reviewing. Agencies can adopt either product independently.

What is the difference between Canonry Embedded, Ads, and Managed?

Canonry Embedded puts client AI visibility inside an agency portal. Canonry Ads compares AI answer gaps with separate demand evidence so agencies and individual advertisers can review possible ChatGPT Ads tests. Canonry Managed runs AEO end to end for businesses and serves as a white-label AEO delivery team for marketing and SEO agencies.

How long until I see results?

It depends on your starting point, market, competition, and how volatile the prompts are. We do not promise a fixed timeline, because AI visibility can shift when models are updated or re-indexed, often without notice. 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; assisted onboarding includes an estimate based on active client volume. Canonry Ads is in private beta. Canonry Managed and the detailed AI Visibility Report are scoped based on the market, site, and execution required.

AI SEO Software & AEO Services | Canonry