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The AI Visibility Engine: how we get businesses recommended by AI

Getting cited isn’t enough. Getting recommended is. Four phases and seven stages that take a business from a $499 baseline audit to month-over-month evidence of where AI recommends you, and what it produced.

See the seven stages

Last updated: October 2026

The System

How does The AI Visibility Engine work?

The AI Visibility Engine runs in four phases and seven stages. Audit finds where you appear across ChatGPT, Claude, Perplexity, Gemini, Grok and Copilot, who gets recommended instead, and which sources those recommendations rest on. Foundation makes your own pages the clearest, most verifiable answer. Authority earns the independent sources AI systems rely on and strengthens the signals that put you on a shortlist. Proof measures citations, mentions, recommendations and share of AI voice against competitors, alongside leads.

The AI Visibility Engine: four phases, seven stages

01 Audit Stages 01–03 Where you appear, who gets recommended instead, and the sources behind it 02 Foundation Stage 04 Your own pages, schema, entity data and crawler access 03 Authority Stages 05–06 Independent sources, and the signals that put you on a shortlist 04 Proof Stage 07 Citations, mentions, recommendations and share of AI voice, tied to leads

The seven stages

  1. 01AI Visibility Audit
  2. 02Competitive Recommendation Analysis
  3. 03Source & Citation Mapping
  4. 04Owned Content Optimization
  5. 05Third-Party Authority
  6. 06Recommendation Optimization
  7. 07Measurement

The shift this system answers is already measured. OpenAI reported ChatGPT passed 800 million weekly users in October 2025. Google says AI Overviews reach more than 1.5 billion people per month (Alphabet Q1 2025 earnings). And Gartner projected a 25% decline in traditional search volume by 2026. Buyers are asking AI who to hire, and the answer is mostly built from other people’s pages: on commercial-intent prompts, NP Digital found 82% of AI citations went to third-party sources and 3% to the brand’s own pages (why a citation isn’t a recommendation).

No one can make an AI system recommend a brand. What The AI Visibility Engine does is improve the quality, authority and availability of the signals those systems rely on, and measure whether recommendations follow.

Phase 01 · Stages 01–03

What happens in the Audit phase?

The Audit phase finds out where you stand and why. We run the questions your buyers actually ask across ChatGPT, Claude, Perplexity, Gemini, Grok and Copilot, record who gets recommended, and trace each competitor recommendation back to the sources that support it. It starts with the AI Visibility Audit, a $499 fixed-scope engagement that ends in a scored report with a prioritized fix list.

  1. 01

    Stage 01: AI Visibility Audit

    Real prompts your buyers type, run repeatedly across all six engines. Buyers don’t just type “dentist Toronto”; they ask which dentist near them is good with anxious patients and open on Saturdays. We map those prompts first, record where you appear, and check schema coverage, entity data and AI crawler access.

  2. 02

    Stage 02: Competitive Recommendation Analysis

    For every prompt where a competitor is recommended and you aren’t, we find out why: which sources support them, what those sources say, and what you’re missing.

  3. 03

    Stage 03: Source & Citation Mapping

    We identify the publications, review sites, directories, communities and pages AI systems keep relying on in your category, and the ones that cite your competitors but not you.

Why it matters

You can’t fix a problem you can’t see. Most owners have never watched an AI answer a buyer question about their category, and the answer often names competitors instead. A citation isn’t a recommendation either: an answer can link to your page and still send the buyer elsewhere. The audit records who gets recommended, and becomes the baseline every later stage is measured against.

What you see

A scored report plus a prioritized fix list, yours to keep whether or not you continue, and a map of the sources behind each competitor recommendation. If you move into the monthly program, the $499 is credited toward your first month, so the audit is never a sunk cost.

Phase 02 · Stage 04

What happens in the Foundation phase?

Foundation makes your own site the clearest, most verifiable answer available. We open crawler access for GPTBot, ClaudeBot, PerplexityBot and the other AI crawlers, deploy JSON-LD schema for the business, its people and every service, align your name, address, phone and credentials everywhere AI checks, and rework key pages so they answer buyer questions directly.

  1. 04

    Stage 04: Owned Content Optimization

    We make your pages the clearest, most specific answer to the questions buyers ask, with structured data that removes any doubt about who you are and what you do. Owned pages earn a small share of citations on commercial prompts (3% in NP Digital’s 2026 study), but NP Digital found they carried the largest lift in AI visibility when they were cited, about 5×.

Why it matters

AI engines only recommend what they can verify. When your website says one thing and your directory listings say another, the model can’t confirm you’re real, so it names a competitor whose data agrees with itself. How a page is written matters too: in the Princeton-led GEO study (KDD 2024), adding citations, quotations and statistics to content lifted its visibility in generative engine answers by up to 40%.

What you see

A before-and-after view of schema coverage, a consistent entity footprint (one name, one address, one phone number, one set of credentials wherever a machine looks) and key pages rewritten to answer the questions your buyers ask.

Phase 03 · Stages 05–06

What happens in the Authority phase?

Authority is where most recommendations are decided, because AI answers are mostly built from other people’s pages. We earn inclusion in the independent sources AI systems rely on, then strengthen the signals that let an AI confidently put you on a buyer’s shortlist.

  1. 05

    Stage 05: Third-Party Authority

    Expert commentary and digital PR in the publications your category trusts, accurate listings and directory profiles, and a review strategy that gets customers to name the specific services they used. No fake reviews and no spam placements: authority comes from being genuinely relevant where your buyers already read.

  2. 06

    Stage 06: Recommendation Optimization

    Consistent entity data, a clear position, and specific, corroborated claims about what you do best, stated in the same terms on your site and in the sources that mention you. The aim is simple: what you say about yourself is confirmed by what others say about you.

Why it matters

Generative engines weigh sources, not just pages. On commercial-intent prompts, NP Digital found 82% of AI citations went to third-party sources. When a buyer asks who to hire, the answer is built largely from reviews, directories, local press, comparison pages and forums. A program that only works on your own site is working on the smaller half of the problem.

What you see

A growing citation list: every third-party page that names your business, tracked as it accumulates month over month, alongside the claims those pages make about you.

Phase 04 · Stage 07

What happens in the Proof phase?

Proof is where the system reports on itself. Every month we re-run your full prompt set across all six engines and track citations, mentions, recommendations and your share of AI voice against competitors, alongside branded search, referral traffic and leads.

  1. 07

    Stage 07: Measurement

    The same buyer prompts, scored the same way as your original audit, so movement is comparable month to month and a regression shows up as fast as a win. We keep four things separate that usually get blurred together: whether you were cited, whether you were named, whether you were recommended, and whether it produced an inquiry.

Why it matters

Rankings you can’t connect to revenue are decoration, and so are citations that never name you. In a June 2026 study by Semrush with Kevin Indig’s Growth Memo, 61.7% of AI citations were “ghost citations”: the answer linked the page but never mentioned the brand. Attribution in AI search is imperfect, so we show you the evidence rather than a single vanity number, and the prompt set evolves as your services and competitors do.

What you see

A monthly report showing which engines name and recommend you, for which services, how that changed since last month, and what it produced in inquiries and leads. You see the same data we do, with no black box.

Side by Side

How is this different from a typical SEO retainer?

A typical SEO retainer sells rankings: content and backlinks measured by positions on a results page. The AI Visibility Engine works toward recommendations: machine-verifiable data, independent sources and monthly six-engine tracking, measured by whether AI recommends your business and whether that produced leads.

Comparison of a typical SEO retainer and The AI Visibility Engine
Typical SEO Retainer The AI Visibility Engine
Primary goal Rank pages on Google for target keywords Get your business recommended when buyers ask AI who to hire
Deliverables Blog posts, backlinks, on-page tweaks, keyword reports Competitor and source analysis, schema and entity fixes, crawler access, answer-first content, third-party authority, review strategy
What's measured Rankings and organic traffic Citations, mentions, recommendations and share of AI voice across six engines, tied to inquiries and leads
Reporting Monthly ranking and traffic dashboard Monthly report: which engines name and recommend you, for which services, and what it produced

You still need sound SEO: Google rankings feed the sources AI engines cite. The AI Visibility Engine builds on that base instead of replacing it.

Industry Playbooks

Where does The AI Visibility Engine run?

The same four phases and seven stages run in every vertical we serve. Only the buyer prompts, schema types and citation sources change. Pick your industry to see the playbook applied to it.

Optometrists Chiropractors Dentists Law Firms Real Estate Med Spas Physiotherapy Accountants Home Services

See what the system has produced for real clients on our results page, or read the guide to choosing a GEO agency in Toronto.

The AI Visibility Engine: frequently asked questions

The AI Visibility Audit takes about two weeks from sign-up to delivered report, and the competitor and source analysis builds on it through the first month. Foundation work, covering crawler access, schema, entity cleanup and your key pages, ships over the first 30 to 60 days. Authority building starts in month two and compounds from there. Proof runs monthly from day one, so you see movement, or the lack of it, every month.
Start with the audit. The AI Visibility Audit is $499, fixed-scope, and the report is yours to keep: a scored baseline plus a prioritized fix list you could hand to any team. If you continue into the monthly program, the $499 is credited toward your first month. Most clients start there.
The monthly program starts at $2,850 per month and covers the Foundation, Authority and Proof phases: owned content and schema work, entity cleanup, third-party authority, recommendation optimization, and monthly six-engine measurement tied to leads. Scope scales with locations and service lines, and pricing is agreed up front, with no surprise line items.
Six: ChatGPT, Claude, Perplexity, Gemini, Grok and Copilot. Together they cover where buyers actually ask for recommendations. OpenAI reported ChatGPT passed 800 million weekly users in October 2025, and Google says AI Overviews reach more than 1.5 billion people per month (Alphabet Q1 2025 earnings). If your buyers use it, we track it.
Each month we record, for each buyer prompt and engine, whether you were cited, whether you were named and whether you were recommended. Then we line that up against your inquiry data: form fills, calls, booking sources and “how did you hear about us” answers. When recommendations for a service rise and inquiries follow, the connection is visible in one report. Attribution in AI search is imperfect, so we show you the evidence rather than a single vanity number.
No. No one can make an AI system recommend a brand, and anyone who promises it is guessing. What we do is improve the quality, authority and availability of the signals those systems rely on, then measure whether recommendations follow.

Every engagement starts the same way: the audit.

The AI Visibility Audit is stage one of The AI Visibility Engine: $499, credited toward your first month if you continue. You get a scored report showing which engines recommend you, which recommend your competitors, and the fastest fixes.