AI Search Visibility Audit.
When search engines and AI systems answer the questions that matter in your space, whose data do they use? We map the answers, trace the sources, and show what it would take for the cited source to be you.
For organizations being paraphrased instead of cited.
Every organization now competes in a layer it can’t see: the retrieval layer, where search engines and AI answer systems decide whose version of the record becomes the answer. Most discover the problem only when a journalist, funder, or policymaker quotes someone else’s weaker number.
The audit makes that layer visible and turns the gap into a prioritized, executable roadmap. The method is the same one behind End The Wait Ontario, whose FOI-verified figures have been cited by OPSEU/SEFPO, CCRW, and national news coverage.
What you receive.
Retrieval map
What ChatGPT, Perplexity, and Google's AI results currently answer for your priority questions, and whose data those answers are built from.
Source-chain assessment
Your load-bearing claims audited for traceability: does each figure link to a primary record a stranger can check in one click?
Citation gap analysis
The sources being cited in your place, and the observable structural differences associated with why they hold the answer today.
Fix roadmap
Which claims to restructure, which pages to build, in what order, scoped so your own team can execute, or we can.
Measurement baseline
A repeatable quarterly retrieval test so movement in AI citations and mentions is tracked, not guessed.
Verified-claims register
A register separating supported claims, interpretations and unresolved questions. Source accuracy, denominators, calculations and freshness are checked within the agreed scope; a citation alone is not validation.
STANDARD SCOPE
- Five priority questions: the ones your customers, funders, or regulators actually ask.
- Three answer systems: ChatGPT, Perplexity, and Google’s AI results, tested in your market.
- Roughly two weeks from kickoff to delivery of the written audit and roadmap.
- Your inputs: the five questions, your load-bearing claims, and access to where those claims are currently published.
Larger question sets, additional systems, or multi-market testing are scoped as extensions. Every engagement is formalized through a written agreement with explicit deliverables and a timeline. AI citations and rankings cannot be guaranteed by anyone; the audit tells you where you stand and what is in your control.
Common questions.
What is an AI Retrieval Audit?
- A scoped diagnostic that answers one question precisely: when search engines and AI answer systems (ChatGPT, Perplexity, Google's AI results) get asked the questions that matter in your space, whose data do they use? We map the answers, trace the sources they cite, and identify what it would take for the cited source to be you.
Who is it for?
- Associations, unions, advocacy organizations, and mid-sized businesses whose credibility depends on their data being found and trusted, especially organizations that publish research, waitlist or program figures, policy positions, or market analysis and keep seeing weaker sources cited in their place.
What do we walk away with?
- A retrieval map of what AI systems and search currently answer for your priority questions, a source-chain assessment of your load-bearing claims, a gap analysis against the sources being cited today, and a prioritized fix roadmap: which claims to restructure, which pages to build, and how to measure movement.
How is this different from an SEO audit?
- This audit focuses on external AI-search answers: which sources are cited, whether your key claims are supported, and how to measure changes. It overlaps with technical SEO and content-quality work. It is not an audit of an internal retrieval-augmented generation system, and it does not guarantee rankings or citations.
Find out whose data the answers are built from.
Tell us the five questions that matter most in your space. We respond to qualified inquiries within two business days and scope a proposal from there.
Before an engagement starts
Know what you are buying.
Organizations with valuable published expertise that is absent, misrepresented or weakly cited in AI answers.
People ask relevant questions, but the answers overlook your evidence or describe it incorrectly.
What you receive
- A dated baseline across five questions and three answer systems.
- A verified-claims register and source gaps.
- Prioritized publishing and technical recommendations.
- A repeatable measurement protocol.
What we need from you
- Five priority questions, intended audiences and relevant public URLs.
- Any existing measurement exports you are authorized to share.
What is not included
- An audit of an internal retrieval-augmented generation system.
- Guaranteed rankings, citations, traffic or answer-system behavior.
- Implementation or ongoing monitoring unless included in the proposal.
How completion is checked
- The agreed observations record question, system, date and conditions.
- Recommendations point to a demonstrable evidence or implementation gap.
- The baseline can be repeated using the supplied method.
- Timing
- Typically about two weeks for five priority questions across three agreed answer systems, subject to access and scope.
- Fees and changes
- A written fixed-fee proposal follows the scope review. Changes to the agreed scope require approval before work proceeds.
- Ownership and handover
- You receive the report, claims register and measurement method. Third-party answer systems remain outside Prior Signal's control.
These are the standard scope boundaries; the signed proposal controls the specific engagement. No ranking, regulatory outcome or third-party behavior is guaranteed.