Free LLM Visibility Checker

Enter your brand name, industry, and optional website URL. The checker queries multiple AI models with prompts your real customers would use. It records whether each model mentions your brand, how prominently you appear, and what context surrounds the recommendation.

You get a visibility score across ChatGPT, Claude, and Perplexity along with a breakdown of which queries surface your brand and which do not. The report flags gaps where competitors appear but you do not. Think of it as SERP tracking for the AI era. Instead of page positions, you are measuring recommendation frequency and sentiment across large language models.

Unlike traditional SEO rank trackers, this tool measures a fundamentally different signal: LLM visibility depends on brand authority, content structure, and how often authoritative sources mention you. Backlinks still matter, but the weighting is different. Models prioritize brands they can confidently recommend.

Over 100 million people use ChatGPT weekly. Perplexity is growing fast. Claude handles millions of research queries per day. When someone asks an AI model "what is the best tool for X," the answer replaces the entire first page of Google. You either get recommended or you do not exist.

AI search optimization requires a different playbook than traditional SEO. Models learn from crawled web data, but they weigh signals differently. Original research gets cited more than rehashed blog posts. Structured content with clear schema markup is easier for models to parse. Consistent brand mentions across authoritative sources build the brand authority that models use to decide recommendations.

The brands investing in generative engine optimization now will own the AI recommendation layer for years. Models are sticky. Once a model learns to recommend your brand, that recommendation persists across millions of conversations. Early movers build a moat that is expensive to displace.

The report scores five dimensions. Mention frequency tracks how often your brand appears in AI responses across different query types. Recommendation quality measures whether you are mentioned as the top pick, an alternative, or just listed in passing.

Sentiment analysis flags whether AI descriptions of your brand are positive, neutral, or negative. Competitor comparison shows who else appears for the same queries and how their visibility stacks against yours. Gap identification pinpoints the high-value queries where you are invisible but should not be.

Use the AI Extractability Scorer to fix content structure issues flagged in this report. Use the Brand Authority Analyzer to strengthen the authority signals that drive AI recommendations. Together, these three tools give you a complete AI readiness picture.