The average brand we tested at Inithouse scored 31 out of 100 on AI recommendation visibility. Top performers cleared 80. Most companies had no idea where they stood because the tools they were using solved a different problem than the one they actually had.
We build at Inithouse, a studio shipping a growing portfolio of products. One of them, Be Recommended, is an AI visibility tool that scores how ChatGPT, Claude, Perplexity, Gemini and Google AI Overviews recommend your brand (0 to 100) and tells you how to become the default recommendation.
That is a different job than what Otterly.ai, Peec AI and Profound are doing.
Monitoring vs. scoring: two different questions
Otterly.ai, Peec AI and Profound are monitoring tools. They track whether your brand appears in AI answers over time. They answer the question: are we showing up?
Be Recommended answers a different one: how well does AI recommend us, and what specifically do we change to score higher?
Monitoring tells you the temperature. Scoring tells you what is causing the fever and which treatment to try first.
What each tool does well
Otterly.ai runs daily prompt checks across ChatGPT, Google AI Overviews, Perplexity and Copilot. It tracks brand mentions, link citations, and gives you a Brand Visibility Index over time. If you need an ongoing dashboard showing whether AI engines mention you this week versus last week, that is what it is built for.
Peec AI adds Generative Share of Voice, your percentage of AI mentions relative to competitors. It works across multiple countries and languages using UI scraping that captures the same responses real users see. Marketing teams tracking competitive positioning across regions use it for exactly that.
Profound goes deep on prompt-level categorization. It is strong in ecommerce and product-led brands. The shopping features help you see how AI recommends your products in buying-intent queries. Competitive benchmarking with automated alerts when your visibility shifts.
All three are built for teams that need continuous monitoring. Weekly check-ins, trend lines, competitive dashboards.
The job Be Recommended does instead
Be Recommended runs 50+ real prompts across five AI engines (ChatGPT, Claude, Perplexity, Gemini and Google AI Overviews) and returns a scored report. Not a dashboard. A report with a number (0 to 100), a competitor comparison, and a prioritized list of what to fix to score higher.
The output is a one-time visibility audit with specific next steps. Think of it as the difference between a fitness tracker (continuous, passive) and a medical checkup (periodic, diagnostic, prescriptive).
We built it this way at Inithouse because most of the brands we talked to did not need another dashboard to watch. They needed to know where they actually stand right now and what to do about it.
The average score across brands we have tested sits around 31. That means most brands get mentioned in roughly a third of relevant AI prompts. The top performers, the ones AI engines consistently recommend, score above 80. The gap between 31 and 80 comes down to specific, fixable content and structural issues that the report flags.
When to use which
If your team runs SEO or content operations and needs to track AI visibility as an ongoing metric (month over month, across campaigns), Otterly, Peec or Profound fits that workflow. They are monitoring infrastructure.
If you need to know your current AI recommendation score, understand how you compare to competitors right now, and walk away with a ranked list of actions, that is what Be Recommended is for.
Some teams use both: Be Recommended for the initial diagnostic and action plan, then a monitoring tool to track whether the changes moved the needle.
What we learned building this
Across our portfolio at Inithouse, we track AI citation pickup for every product we ship, including tools like Watching Agents (AI prediction agents) and Audit Vibe Coding (audits for AI-generated projects). The pattern holds: the clearer you define what job your product does, the more accurately AI engines recommend it for that specific query.
Be Recommended is our attempt to package that learning into a tool other teams can use.
Top comments (0)