LLMrefs

Marketers, SEOs and agencies built their strategies around traditional keyword search, but search is shifting to conversational AI engines that use large language models to interpret intent and context. These AI models are non-deterministic and there are an infinite number of possible prompts users could ask, making it impractical to manually track how a brand is mentioned across every AI conversation. Traditional SEO tools do not show whether a brand is cited or recommended inside ChatGPT, AI Overviews, Perplexity or other AI answer engines, or which sources those engines are pulling from. Without this visibility, brands cannot tell how they compare to competitors in AI-generated answers or where their content gaps and outreach opportunities lie.

LLMrefs lets users track keywords rather than individual prompts, then automatically generates fan-out prompts based on real conversations users have with AI chatbots and aggregates the responses. The dashboard shows brand rankings by share of voice, position and citation count, benchmarked against named competitors, across AI search engines including ChatGPT, ChatGPT Search, Google AI Overviews, AI Mode, Gemini, Perplexity, Claude, Grok, Copilot, Meta AI and DeepSeek, with geo-targeting across 50+ countries and 20+ languages. It also surfaces the specific source URLs (e.g. Reddit, Wikipedia, YouTube, Amazon) that these engines cite, weekly automated visibility reports, monthly AI prompt volume estimates, and export via CSV or API. Additional tools include an AI crawlability checker, a Reddit threads finder, and an LLMs.txt generator. The platform is built for agency use with unlimited projects, unlimited team seats and client dashboards under a single subscription.

The text argues that search itself has become conversational and fragmented across multiple non-deterministic AI models, making traditional SEO strategies less effective and creating a need for a new kind of tracking built for this shift.