LLM Search Console

LLM Search Console is the first GEO (Generative Engine Optimization) platform that tracks the complete chain from AI crawls to final mentions in large language model responses. Designed for SEO professionals, brand managers, and digital marketers, it solves the problem of measuring brand visibility across AI-powered search engines like ChatGPT, Claude, Gemini, Perplexity, Mistral, and Grok.

What Makes LLM Search Console Stand Out

• Multi-LLM tracking: Monitor mentions and citations in ChatGPT, Claude, Gemini, Perplexity, Mistral, Grok, Copilot, and more from a single dashboard.
• Visibility Score & Share of Voice: Get a unified metric of your AI presence and compare your share of voice against competitors.
• Reverse Lookup: Discover which prompts already include your brand—a unique feature for identifying untapped opportunities.
• Citation Chains: Trace the source origins that LLMs use to generate responses about your market.
• AI crawler pixel: A lightweight tracking script to see which AI bots crawl your site and how often.

Who Should Use LLM Search Console

• SEO and GEO specialists wanting to understand and optimize their brand's presence in AI-generated search results.
• Brand managers needing to monitor brand mentions and sentiment across multiple LLM platforms.
• Content and marketing teams aiming to improve their content's likelihood of being cited by AI assistants.

Frequently Asked Questions

What is LLM Search Console?

LLM Search Console is a GEO analytics platform that tracks how often and in what context your brand appears in responses from large language models like ChatGPT, Claude, and Gemini.

How does it track citations?

It uses a combination of automated prompts and a tracking pixel that detects AI crawler activity, then matches crawls to generated mentions across supported LLMs.

What are the limitations?

Coverage depends on public API availability and may not capture all private or internal LLM instances. Tracking is limited to the prompts and sources the platform can systematically query.