See what your page tells search and AI systems.

Review topic focus, entity clarity, semantic coherence, answer structure, and connected JSON-LD in one evidence-backed report.

  • Four clear findings, not an unexplained score
  • Three prioritized actions tied to page evidence
  • Reviewable schema and an ungated Markdown report

One page at a time

Run your free analysis

URL or pasted content
Advanced options

Override the detected topic, refresh source data, or add modeled question coverage.

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One page, one prioritized report

From page content to a reviewable action plan

1

Read the page

Identify the main topic, important entities, headings, and answer patterns.

2

Assess clarity

Separate topic focus, entity identity, coherence, and answer structure.

3

Review the artifact

Work through three actions, then inspect the connected JSON-LD before use.

Questions before you run a page

SEO & AI-Search FAQ

Why is it called The Ontologizer?+
An ontology is a shared vocabulary for describing the things in a subject area and how they relate — Person, Organization, Product, author, offers, and so on. Schema.org is the biggest ontology on the web: a vocabulary Google, Microsoft, Yahoo, and Yandex agreed to so a machine reading your page can tell that “Apple” means the company and not the fruit, and that a review belongs to a specific product.

Ontologizer turns your unstructured page content into ontology-friendly structured data. It finds entities, resolves them against Wikipedia, Wikidata, and Google's Knowledge Graph, and builds JSON-LD aligned with supported schema.org types. The report shows the facts it used, what it omitted, and what needs review.
What is entity-based SEO and why does it matter?+
Search systems use more than keywords. They can also map content to entities (people, places, products, concepts) and their relationships. Ontologizer shows which entities it could support with page context and external identifiers, plus which matches need human review.
How is this different from a regular schema generator?+
Most schema tools ask you to fill out a form and spit out JSON-LD from the fields you typed in. Ontologizer reads your actual page, resolves entities against Wikipedia, Wikidata, and Google's Knowledge Graph API, and uses those sameAs references to build schema that ties your content to external identifiers search engines already trust.
What is AI Query Coverage and should I use it?+
AI Query Coverage models five to eight adjacent questions a person might ask about the page topic. It then checks those questions against supplied page chunks and cites the supporting chunk IDs. These are modeled questions, not actual Google searches or Search Console data.
Does adding JSON-LD actually help with AI-powered search?+
Structured data can reduce ambiguity, but it is not a ranking guarantee. It works only when the markup matches visible page facts. Pair JSON-LD with clear on-page naming and supporting content, then review it in Schema.org Validator and Google Rich Results Test.
What do you do with my data?+
We log analysis lifecycle data, including the URL, completion status, provider usage, and cost, to operate and improve the tool. If you're signed in, runs are logged against your account, and Search Influence may follow up with people who might want help shipping their findings. If you're using your own API keys without an account, runs are logged without an account identifier.

Your API keys are stored in your browser, sent through the analysis routes for the requested provider call, and not persisted by the application. If you do not want a follow-up, use the Feedback button to tell us.
What should I do with the recommendations?+
Start with the three actions in the Overview. Each action includes an observation, page evidence, effort, and confidence. Review the detailed checks before changing copy or publishing schema. If you want implementation help, Search Influence can help you ship it.