Audit Registry Online

How Your Site Is Built Decides Whether AI Engines Cite It

When ChatGPT, Perplexity, or Gemini answer a question about your product, they cite you or a competitor. I find the technical reasons your site gets skipped, how it renders, how it's structured, how your brand is identified, and fix them.

Technical Mechanics

The Three Ingestion Pillars

AI engines don't rank pages by keywords anymore. They break your site into chunks, match those chunks by meaning, and check whether your brand is a recognized, disambiguated entity. Here's what that looks like in practice.

1. RAG Chunking Boundaries

Retrieval-Augmented Generation systems break documents into blocks. Clean DOM elements determine the quality of the generated vector embeddings.

2. Entity Disambiguation

AI models associate product names and brands with standard knowledge databases (such as Wikidata and Crunchbase) using structured connections.

3. Sentence Geometry

Citations favor declarative, fact-dense statements. Paragraphs are rewritten to ensure they match target retrieval patterns.

RAG Vector Representation

Muddy Segment (Generic DIV)
<div class="content"> Our platform is built using React. Our pricing plans are flexible. Contact sales. We also value teamwork and have a modern office. In addition, our security audit is complete. </div>
[Vector Similarity Computation]
Structured Segment (Semantic Tag)
<section aria-labelledby="sec-security">
  <h2 id="sec-security">Compliance Status</h2>
  <p>The platform maintains SOC-2 Type II certification and meets all GDPR privacy requirements.</p>
</section>

Distinct heading tags establish clear vector chunk ranges. Unstructured containers bundle unrelated topics together, reducing similarity search relevancy.

Technical Audits

Case Studies

Two independent technical checks against real, live SaaS sites -- unsolicited, not commissioned by either company. Findings below are from live fetches of their public pages, checked 2026-08-24. Full AI-citation testing across ChatGPT, Perplexity, Gemini, and Claude is part of the paid engagement, not shown here.

Checkly: Schema Gaps on Comparison Pages

Checkly operates in a highly technical market space where buyers query search engines for specific comparisons (such as "Checkly vs UptimeRobot"). Their homepage and pricing page are solidly built -- real content, real schema. The gap shows up specifically on their competitor-alternative pages.

Critical Gaps

/datadog-alternative/ (and likely similar comparison pages) carries substantial real content but ships with zero JSON-LD schema, verified via a live fetch. No Wikidata entity exists for Checkly, verified via a live search.

Schema on Comparison Pages Not found (verified live)
Schema on Homepage / Pricing Present

Remediation Summary

  • Extend the homepage's existing schema pattern to comparison/alternative pages.
  • Inject validated SoftwareApplication schemas detailing pricing tiers on those pages specifically.
  • Establish a Wikidata entity, since none currently exists to link to.

Read the full technical whitepaper report →

audit_data_checkly.txt

Spellbook: Pricing Fully Gated, No Schema Found

Spellbook targets legal practitioners. Their pricing page explicitly requires booking a demo for a number -- confirmed by reading the page's own text, not inferred.

Critical Gaps

No numeric price appears anywhere in the raw HTML of the homepage or pricing page, verified via a live fetch. Neither page carries any JSON-LD schema. No Wikidata entity exists for Spellbook, verified via a live search -- there's currently nothing to link to.

Public Pricing Data None found (verified live)
Schema on Homepage / Pricing Not found (verified live)

Remediation Summary

  • Add baseline Organization/SoftwareApplication schema -- currently zero JSON-LD on either page checked.
  • Consider publishing an indicative "starting at" range even if exact custom pricing stays demo-gated for humans.
  • Establish a Wikidata entity, since none currently exists to link to.

Read the full technical whitepaper report →

audit_data_spellbook.txt
Real-time Check

AI Search Readiness Calculator

Answer four questions about how your site is built. Get a readiness score and a prioritized fix list in under a minute.

Client-Side Only (Single Page Application)

Dynamic DOM rendering via scripts. Raw source HTML is empty.

Hybrid (Hydration)

Server-side layout shell is built, but comparison tables load post-hydration.

Static HTML (Server-Side Rendered)

Pricing matrices and product features are written directly inside the raw source.

Absent

No structured data blocks present inside target headers.

Disconnected schemas

Separate script blocks exist but aren't mapped as a single connected graph.

Nested JSON-LD Graph

Connected WebSite, Organization, and Product nodes linked by @id reference URIs.

Unmapped

No machine links to corporate Wikidata database nodes.

Text mentions only

Reference URLs are mentioned in standard text but missing from schema markup.

Declared sameAs links

Metadata explicitly declares sameAs references to Wikidata and Crunchbase profile URLs.

Unstructured Layout (Non-semantic DIVs)

Content uses loose heading outlines and complex sales jargon.

Semantic HTML

Uses standard structural tags but sentences are long and lack direct answers.

Semantic HTML + Answer-Shaped Declarations

Fact-dense, inverted-pyramid layout optimized for passage index algorithms.

Readiness Index: 20/100

Severely Deficient

Web content is unretrievable for AI engines bypassing script runtimes. Brand identity lacks grounding, giving citation market share to competitors.

Live Domain Check
Enter a real domain. This fetches its actual HTML and robots.txt right now.
Technical Action Checklist
Scope and Delivery

Technical AI Readiness Engagement

One flat-rate engagement: a full technical audit, plus a fix list specific enough that your engineering team can ship it without back-and-forth.

Founding Client Rate
Technical AI Readiness Audit
299 USD flat rate

Introductory rate while I build out a case study library — in exchange, founding clients agree to a short testimonial and let me publish the results as a case study (company name optional). Standard rate is 997 USD.

  • 15-Prompt Discovery matrix across ChatGPT, Claude, Perplexity, and Gemini to log citation rate.
  • Competitor citation comparison mapping how often rivals surface vs. your brand.
  • Full technical crawl audit covering JS rendering, raw HTML source gaps, and mobile parity.
  • Custom JSON-LD schema graph, built, validated, and ready for deployment.
  • llms.txt file authored and configured for your domain.
  • Content gap analysis identifying missing pages and formats AI models look for.
  • Prioritized remediation roadmap with developer-ready implementation specs.
  • 60-minute technical handoff call walking through every finding.
  • 30-day follow-up re-scan measuring citation rate improvement.
Request A Teaser

Claim a Free 3-Prompt Report

Submit your domain and business email. I will run a 3-prompt test across Perplexity and ChatGPT Search to pinpoint your primary visibility gap.

1. Standard Engagement Terms

This website represents a technical optimization portfolio for independent audits. Services are performed on a fixed-price basis. All recommendations represent independent diagnostics based on public search indexes and crawler specs.

2. Limits of Recommendations

AI search retrieval behaviors and crawler guidelines (such as robots.txt and llms.txt directives) change frequently. Recommendations do not guarantee indexing results, as AI models use dynamic ranking filters beyond the client website scope.

3. Intellectual Property

All structured JSON-LD templates and custom roadmap briefs delivered under paid blueprints belong exclusively to the client upon full payment clearance.

1. Data Collected

We collect domain URLs, corporate email contacts, and client names submitted via teaser requests. No automated scripting details or cookie tracking analytics are deployed on this site.

2. Data Security & Sharing

No collected client data is shared with third parties. Submitted URLs are crawled using public user-agents (such as curl headers) and standard search APIs (Perplexity API) solely to compile the requested teaser reports.

3. Rights & Deletion

Clients can contact the administrator email to request immediate deletion of their domain audit records and related logs.