AI Search

People aren't Googling anymore. They're asking AI.

Get Recommended by ChatGPT & AI Search
Playbook

The GEO playbook - how to get named by AI in 90 days.

An 8-chapter field guide covering entity engineering, citation stacking, retrieval mechanics, and share-of-voice measurement. Everything we do, in the open.

What you get

What you get

Entity-first thinking

AI reasons over entities, not pages. Everything starts here.

Retrieval mechanics

Understand how grounding works and you understand GEO.

Citation surface

The 25–40 sources every AI model actually pulls from.

Model-specific tuning

ChatGPT, Gemini, Claude, Perplexity - different citation appetites.

Share-of-voice tracking

Prompt-level measurement. Not rankings.

Durable signals only

Nothing that breaks on the next model update.

Chapters

01

Why GEO exists

Google's AI Overviews, ChatGPT search, and Perplexity have collapsed the buyer journey into a single AI answer. If your business isn't in that answer, you don't exist. GEO is the discipline of engineering your presence into it.

02

The retrieval loop

Every AI answer runs a retrieval step (grounding) that pulls fresh sources before generating text. The winners are the entities that are (a) unambiguously modeled and (b) present in high-authority sources at retrieval time.

03

Entity engineering

Your business must exist as one canonical entity - same name, same NAP, same schema across every surface. Ambiguity kills retrieval. Every provider, product, service, and location is a linked sub-entity.

04

Citation stacking

Model-specific citation preferences: ChatGPT leans on established publishers and Wikipedia-adjacent authority; Perplexity leans on freshness and diverse sources; Gemini leans on Google's Knowledge Graph. Stack accordingly.

05

Prompt-level tracking

GEO isn't measured in rankings - it's measured in prompts. Pick 30–100 real buyer prompts, run them monthly across ChatGPT, Gemini, Claude, Perplexity, and score share of voice per model.

06

Content that gets retrieved

Retrievable content answers a specific question, cites its own sources, uses semantic H2s, and marks up FAQs, HowTos, and definitions with JSON-LD. Length matters less than density and specificity.

07

Durability over tricks

Prompt injection, review manipulation, and thin-content spam all get penalized on the next model update. Every signal you build should still be valuable a year from now.

08

Reporting your buyers believe

Screenshots from each AI model, side-by-side, month over month. No black-box dashboards, no vanity metrics - just the answers your prospects actually see.

Want us to run this for you?

See the same playbook applied to your business, end to end.

Ready to get recommended by AI?

Allocation is capped. Apply now to see if your business qualifies.