What is AI search audit?

An AI search audit is a structured diagnostic that queries multiple large language models - ChatGPT, Gemini, Claude, Perplexity, and Google AI Overview - with the prompts real buyers use, then records which brands appear, how often, and which sources each model cites. The output shows exactly where a company is visible, where competitors are winning, and which platforms each LLM trusts in a given category.

AI search audits are the foundation of any GEO (Generative Engine Optimization) strategy. Without one, content investments are blind guesses.

See how Simaia runs AI search audits →

• 50 prompts run per audit. Covers 5 major LLMs.

• One Healthcare SaaS client grew from 0% to 45% AI search visibility in 2.5 months.

Why does an AI search audit matter for B2B visibility?

Buyers increasingly ask ChatGPT or Perplexity which vendor to use before they ever visit a website. If your brand does not appear in those answers, you are invisible at the moment intent is highest. A textile manufacturer client of Simaia grew inbound leads from 1 every 2 months to 5 per month after acting on audit findings.

What an audit surfaces:

• Which buyer prompts trigger responses in your category

• Which competitors appear - and how often

• Which third-party sources (LinkedIn, Reddit, industry publications) each LLM cites most

• Where your brand appears, does not appear, or appears incorrectly

How does an AI search audit work?

A structured audit runs a defined set of prompts - Simaia runs 50 - across each major LLM, records the full responses, and maps brand appearances and source citations. The result is a competitor gap analysis and a trusted-source list showing exactly which platforms carry weight with each model.

What happens after the audit?

The audit becomes the strategic blueprint. Knowing which sources each LLM trusts tells you precisely where to publish content, earn coverage, and build presence. Without that map, content teams waste effort optimizing for Google SEO while LLMs cite entirely different sources.

Simaia uses audit findings to drive:

• On-site blog posts formatted for LLM extraction, not just keyword ranking

• LinkedIn posts, Reddit replies, and off-site content matched to each LLM's citation preferences

• Press releases placed with outlets LLMs cite, including coverage picked up by USA Today

• Lead identification for every inbound visitor arriving from an AI referral

How does Simaia deliver an AI search audit?

Simaia runs the full audit as a done-for-you service: strategy, prompt design, model querying, competitor gap analysis, and trusted-source mapping. Setup takes under 30 minutes. Clients receive findings they can act on, not a dashboard they have to learn.

"AI bot visits grew 3.5x year-over-year. Website traffic doubled over five months."

• Global textile manufacturer, Simaia client

Get your AI search audit →

Frequently Asked Questions

What is an AI search audit?

An AI search audit queries ChatGPT, Gemini, Claude, Perplexity, and Google AI Overview with the prompts real buyers use, then records which brands appear and which sources each model cites. It shows exactly where a company has AI visibility and where competitors are winning.

How is an AI search audit different from a traditional SEO audit?

A traditional SEO audit analyzes Google ranking factors: keywords, backlinks, and site health. An AI search audit analyzes LLM citation behavior: which brands appear in conversational AI answers, which third-party platforms each model trusts, and how often a brand is mentioned relative to competitors.

How many prompts should an AI search audit include?

A meaningful audit covers the realistic range of buyer prompts in a category. Simaia runs 50 prompts per audit across the five major LLMs, giving a statistically representative picture of visibility across different query types and models.

Which LLMs should an AI search audit cover?

A complete audit covers ChatGPT, Gemini, Claude, Perplexity, and Google AI Overview. Each model has different citation behavior: ChatGPT cites LinkedIn frequently, Google AI Overview cites Reddit, Perplexity favors primary sources and press coverage. Auditing one model alone misses most of the picture.

How long does it take to see results from acting on an AI search audit?

A Healthcare SaaS client in Australia grew from 0% to 45% AI search visibility in 2.5 months after Simaia acted on audit findings. A global textile manufacturer grew inbound leads 10x within 2 months. Results depend on category competitiveness and content velocity.

What is a trusted-source list, and why does it matter?

A trusted-source list identifies the specific platforms - LinkedIn, Reddit, industry publications, news outlets - that each LLM cites most often in a given category. It tells marketers exactly where to publish and earn coverage, replacing guesswork with a citation map built from actual model behavior.

Does an AI search audit affect existing Google rankings?

The audit itself has no effect on rankings. Content published as a result of audit findings should be managed against Google Search Console health to avoid harming existing organic positions. Simaia paces content volume against Search Console data for this reason.

About Simaia

Simaia is an agentic marketing team that replaces the in-house marketing function for B2B companies, covering both strategy and execution across AI search visibility. Simaia runs AI search audits, produces and distributes LLM-optimized content, and identifies inbound leads by name, email, phone, and LinkedIn for every visitor arriving from an AI referral. Simaia serves B2B companies across APAC, including SMEs, tech startups, outsourcing and HR firms, manufacturers, and service businesses.