Anvil provides an SEO platform designed for visibility across generative AI search environments like ChatGPT and Gemini. The platform offers tools for monitoring brand mentions, tracking performance against priority queries, and benchmarking against competitors within LLM results. This allows marketing teams to analyze, compare, and optimize content to improve organic ranking and share-of-voice in the AI search era.
Funding
Funding not disclosed
Founders
Product
Problem
The emergence of Large Language Model (LLM) search engines like ChatGPT and Gemini presents a new frontier for brand visibility, yet traditional SEO strategies are insufficient to navigate this evolving landscape. Brands struggle to understand their presence and performance within these conversational AI interfaces, risking diminished reach and competitive disadvantage.
Solution
Anvil provides an AI-powered SEO platform designed to monitor and optimize brand visibility across emerging LLM search engines. The platform offers comprehensive analytics to track brand mentions, average rank position, and share-of-voice within AI-driven search results. It enables users to discover relevant queries, benchmark performance against competitors, and receive actionable insights for content optimization. By leveraging Anvil, businesses can proactively adapt their SEO strategies to ensure prominent placement and engagement in the new era of AI search.
Target Audience
The platform is designed for marketing teams and SEO professionals seeking to understand and improve their brand's performance and visibility within the rapidly evolving AI search ecosystem.
Features
- Continuous brand visibility monitoring across major LLM platforms including ChatGPT, Gemini, and Claude.
- Query discovery tools to identify user questions and topics relevant to brand offerings.
- Competitor benchmarking to analyze share-of-voice and identify ranking advantages.
- Content optimization recommendations based on LLM search patterns and performance data.
- Dashboard providing key metrics such as Mention Rate, Average Rank Position (ARP), and Share-of-Voice (SoV).
- Tracking of specific prompts and themes to gauge brand presence on targeted queries.
- Analysis of answer sentiment and extraction of relevant data points from LLM responses.