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Setting up

Start measuring your brand visibility.

Start here

Follow our quickstart guide.

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What you can do with Conatus AI

  • Benchmark your brand: Compare how your brand stacks up against competitors in AI mention rates to identify visibility gaps and opportunities.
  • Inform your content strategy: Discover what types of content are most likely to be cited by AI in your industry, enabling you to make data-driven decisions about your content creation.
  • Shape brand perception: Understand what AI tells your prospects about your brand. Refine your content to ensure AI’s perception aligns with your messaging, so prospects receive accurate and favorable information.

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What you’ll see in Conatus AI

  • AI mention probability: The percentage of AI responses that mention your brand across tracked prompts.
  • Frequently cited domains & URLs: A ranked list of domains and URLs with the highest probability of being cited in AI responses, helping you identify authoritative sources in your space.
  • AI brand positioning: Analysis of how AI describes the strengths and weaknesses of your brand compared to competitors.
  • User takeaways from AI search results: A synthesized summary of what users learn about your brand based on AI responses, highlighting key messaging and potential gaps.
  • Raw AI search results: Individual sample AI responses scraped from AI search platforms, allowing you to review actual conversations your prospects might see.

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How Conatus AI works

  1. Define your prompts: You specify the prompts you want to track—these are the questions your prospects might ask AI platforms.
  2. Automated data collection: Conatus uses advanced UI scraping technology to run your specified prompts on AI platforms like ChatGPT and Perplexity, simulating real user interactions. We collect the responses exactly as they appear to users.
  3. Regular sampling: For each prompt, Conatus collects 20 sample responses per AI platform every week. For example, if you track responses across 4 AI platforms, Conatus analyzes 80 sample responses per week per prompt. This sampling approach is essential because LLMs are non-deterministic. Each response can vary, so analyzing multiple outputs provides a more accurate probabilistic view of how your brand appears in AI search results.
  4. Comprehensive analysis: Based on the collected sample responses, Conatus analyzes mention rates, citation patterns, and response synthesis to summarize how AI describes your brand and identify trends over time.
We do NOT use AI platforms’ search APIs because they don’t guarantee consistency in format and data sources with what your prospects see in chat interfaces. UI scraping simulates the actual user experience, ensuring the data reflects what your prospects encounter when interacting with AI platforms.