Retrievable Content for AI Crawlers & Agents: Ahava’s Guide

Is your content “retrievable” for AI crawlers?

We all want to show up in as many AI answers as possible. Which means publishing high-quality conversational content that’s easy for AI to interpret … but everyone knows it’s not that simple.

AI citation optimization is as much about the backend of your site as the front-end. You probably don’t need to own the technical side of your content ops, but you do need to understand how it works and whether your content is positioned to be discovered.

We field a lot of questions about this topic, so we called in our friend Tim Voyles at our sister agency, HealthStack Partners, to give you some clear answers. Let’s get into it.

What does it mean for content to be retrievable for AI?

Retrievable content is data that can be found, accessed, and understood by search engines and AI. To be retrievable, content needs to be:

• Crawlable: Bots are permitted and technically able to access the URL.
• Indexable: Search systems can store and consider the content for results.
• Extractable: Systems can isolate and interpret the relevant facts.

The 3 bullets alone don’t guarantee AI visibility — it also takes relevance and trustworthiness. But retrievability, aka making your content accessible, is the first hurdle to clear on the way to getting your content cited and used in agentic experiences.

Retrievable vs. non-retrievable content

What makes web content easy for AI to crawl and retrieve — or not so much? Here are the elements to look for in your own content:

How can content tags help AI retrieve your content?

Tags are labels applied on the backend of your systems to describe and group content. They support website search, filters, and dynamic functionality (such as related content recommendations).

Internal CMS tags aren’t automatically visible to external AI systems. But when your content or structured data reflects the relationships between those tags, it helps AI understand relationships between key information.

For example, you might tag a cardiologist with:

• Cardiology
• Heart failure
• Atrial fibrillation
• Specific location
• Accepting new patients
• Telehealth available

These tags connect the physician to their specialty, services, and locations inside your CMS. Reflecting those connections in visible content or structured data helps AI interpret the information to answer complex queries, like “Help me find a doctor near Baltimore who’s accepting new patients and has experience treating AFib.”

Can AI systems read and cite PDF content?

Some AI systems can process PDFs, and search engines can index PDFs that use machine-readable text. But even if a PDF is technically “readable,” it doesn’t necessarily mean that systems will interpret the information accurately.

Here’s why:

• Design could impact readability behind the scenes: Complex layouts and missing document tags can make it difficult for AI to connect headings, paragraphs, tables, and other information.
• The format hinders relationship interpretation: PDFs often cover several subjects, limiting your ability to link directly to a specific answer or connect it with related physicians, services, and locations.
• PDFs lead to content management issues: For example, if you publish an updated version without sunsetting the old one, AI systems may come across conflicting information.

Our advice: Publish essential info as an HTML page whenever possible. Offer the PDF as a downloadable companion for people who want to save, share, or print it.

How to make your website more accessible to AI

So what has to exist on your website for AI and agents to accurately extract your information? Here’s what you need, in nontechnical language:

• Dedicated pages: Give each physician, service, location, and product its own unique URL.
• Strong templates: Create templates for physician, specialty, treatment, condition, location, and product pages. These templates should include guidance around clear titles and headings, separate CMS fields for important details, and built-in tags and schema markup (to ensure they’re implemented correctly every time).
• Structured data: Add labels, tags, and schema markup to key URLs, including physician bio pages, location pages, and specialty pages. Check with IT to make sure your schema is customized. (It needs to be, but very rarely is.)
• No barriers: Make essential information available without requiring a search or form. Also, turn important PDF content into HTML pages.
• Crawler access: Confirm that priority pages aren’t blocked by robots.txt, a noindex directive, or other technical settings.
• Consistent information: Establish one reliable source for details such as physician locations, clinic hours, and scheduling options. Assign responsibility for correcting conflicts and reviewing information regularly.
• Relationship mapping: Add links between content about related physicians, services, conditions, and locations.
• Sitemap inclusion: Include important physician, service, treatment, and location URLs in your XML sitemap.

Time to make friends with IT

We’re big advocates of befriending folks across departments. (ICYMI, we wrote a whole series about why.) This work absolutely requires it.

Positioning your content for AI retrievability takes an open dialogue with the technical stakeholders who can help, whether that’s IT, your web team, or an outside vendor. Bring your understanding of patients — the information they need and how they interact with it — and let your technical team help you make that information accessible.

How to tell whether AI can access and extract your content

Before bringing in technical stakeholders, do some homework:

1. Search Google for your org’s name and specific physicians, services, and locations. Ensure your pages come up.
2. Ask AI questions about your organization, physicians, services, and locations. Check the answers for accuracy, down to the specialized treatments you offer and the hours of different clinics. (Note: AI answers come from a range of sources, so accurate information doesn’t necessarily prove that AI can access your website. Treat this as a spot-check of your overall digital presence.)
3. Compare information across platforms for consistency. Do external agents, your website, and your app all agree on answers?
4. Look for warning signs. Missing pages, important info locked up in PDFs, and outdated information appearing before more current information can all indicate retrievability problems.

Google Search Console, Screaming Frog, Google’s Rich Results Test, and Schema.org Validator can help you check indexability, identify blocked pages, and evaluate structured data.

Document what you find, including examples of pages that aren’t showing up in search or specific searches where systems are sharing inaccurate information about your org. These are helpful starting points to explore with your technical team.

What comes next?

Remember how retrievability is just one hurdle in the AI visibility sprint? The next is interoperability: ensuring your systems can “talk to each other” or exchange information (so you don’t have to manually reenter the same data everywhere).

Next up: How to get your content to appear consistently across systems, apps, and portals.