Service 02 · Emerging

AI Search Visibility

Engineered for ChatGPT, Perplexity, Gemini, and the citation layer of the next search era. This is where most SaaS sites are completely invisible right now — and where the next 5 years of compounding distribution will be earned.

Citation surface
4–10×
Increase in AI-citation frequency across tracked queries within 6 months
Coverage window
6–12 months
Where the system establishes durable citation surface across major LLMs
01 · The problem

Most SaaS sites are invisible to AI search

Run a query in ChatGPT or Perplexity about your category. Watch which sources get cited. If your site isn’t one of them, you’re not in a “ranking lower” situation — you’re not in the index at all for the retrieval layer that’s replacing traditional search.

The reason isn’t mysterious. LLMs retrieve content using different signals than Google: chunkability, entity disambiguation, source authority, and retrievable structure. Most sites are built for one game and showing up to a different one. Being good at traditional SEO doesn’t make you cite-able.

02 · The approach

Engineering for retrieval, not just ranking

I treat AI search visibility as a structural engineering problem with three core levers: chunkability (how your content gets segmented during retrieval), entity signals (whether LLMs can identify what your content is about), and source-authority architecture (whether retrieval systems treat you as a credible citation).

The engagement starts with citation surface audits across the major LLMs for your category queries. From there we design the chunking model, entity disambiguation strategy, and the structural changes that make your existing content cite-able — without rewriting it from scratch.

This isn’t about gaming the system. The systems that earn AI citations are the same ones that demonstrate genuine functional authority. The work is structural, not promotional.

03 · What’s included

Deliverables

AI-citation audit

Citation surface diagnosis across ChatGPT, Perplexity, and Gemini for your category queries. The honest map of where you currently sit in the retrieval layer.

Chunking architecture

How your existing content should be structured so retrieval systems can extract cite-able segments. Includes a content restructuring playbook.

Entity disambiguation strategy

How to make your brand, products, and topics unambiguous to LLM retrieval. Schema, knowledge graph signals, and source authority architecture.

Citation-ready content framework

Editorial rules for new content so it earns citation surface from day one. Brief templates and quality bars your team can use immediately.

AI-search tracking system

A monitoring setup so you can see citation surface changing month over month. Includes the dashboard, the query set, and the review cadence.

Team handover & playbooks

Operating documentation so your team can run the AI-search optimisation loop after the engagement ends. The system survives without me.

04 · Process

What 12 weeks looks like

Weeks 1–2

Citation audit

Diagnose current AI-citation surface across major LLMs. Identify which queries you already win and where the gaps are.

Weeks 3–4

Architecture design

Chunking model, entity disambiguation strategy, schema layer, source authority architecture.

Weeks 5–7

Implementation

Working alongside your team to restructure key pages, implement schema, and ship the citation-engineering changes.

Weeks 8–10

Validation & handover

Re-run citation surface tests. Document what moved. Hand over the monitoring system and team playbooks.

05 · Engagement

Pricing & structure

Option 01

Citation audit

$5,500
3-week engagement

Full AI-citation surface diagnosis and 90-day improvement roadmap. Your team executes.

  • AI-citation audit across LLMs
  • Chunking & entity gap analysis
  • 90-day improvement roadmap
  • Async support during build
Most chosen Option 02

Visibility sprint

$11,000
10-week engagement

Full architecture build, implementation support, and the monitoring system. The standard engagement.

  • Everything in Citation audit
  • Chunking architecture rebuild
  • Entity disambiguation implementation
  • Schema & structured data layer
  • AI-search monitoring system
  • Team enablement & playbooks
Option 03

Retainer

$5,000/mo
3–6 month retainer

Ongoing AI-search operator — monthly citation reviews, content restructuring, and architecture refinement.

  • Everything in Visibility sprint
  • Monthly citation reviews
  • New content cite-ability QA
  • Architecture refinement loops
06 · Proof

A system in action

Case study · AI Search Experiments

Engineering for the ChatGPT and Perplexity citation layer

“Six months of structured experiments testing what makes content cite-able by ChatGPT, Perplexity, and Gemini. The chunking model, entity signals, and source-authority patterns I now use in engagements.”

340 Queries tracked
4.2× Cite-rate lift
5 Models tested
07 · Common questions

FAQ

For most SaaS at scale, yes — and increasingly so. AI search now drives 15–25% of high-intent discovery for many categories, growing fast. The question isn’t whether it’s worth it; the question is whether you want to be early or late to the citation surface in your category.
Traditional SEO optimises for ranking in a search results page. AI search optimisation engineers for being cited inside generated answers. Different retrieval mechanisms, different signals, different structural requirements. There’s overlap, but they’re not the same discipline.
No. Prompt engineering happens at query time and is invisible to retrieval systems. What matters is how your content is structured, chunked, and signalled to the indexing layer — which is upstream of any user query.
A tracked query set (typically 50–200 queries relevant to your category), monthly citation snapshots across ChatGPT, Perplexity, and Gemini, plus the structural diagnostics that predict citation surface lift. The data isn’t perfect but it’s directionally reliable.
Then we have a bigger conversation. Citation surface largely requires retrievable content. Gating high-value content blocks AI visibility by definition. The strategic question becomes which content stays gated and which becomes citation infrastructure.

Get on the citation surface before your competitors do.

I take 2–3 AI Search Visibility engagements per quarter. If you want to talk through what AI search looks like for your specific category, let’s set up a call.

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