The AI recommendation landscape now directly affects pipeline. When a prospect asks ChatGPT "what's the best tool for X," the answer shapes their shortlist before they ever open Google. The average brand we've scored at Inithouse sits around 31 out of 100 on AI visibility. Top performers hit 80+. Monitoring how AI models talk about your brand is becoming as routine as tracking search rankings.
Several tools address this problem. Otterly.ai and Profound are two names that come up often. At Inithouse, we built Be Recommended to solve the same problem from a different angle. Here is where each tool fits and where they diverge.
What these tools actually do
All three let you see how AI models mention (or ignore) your brand. The category goes by names like "AI visibility monitoring" or "GEO (Generative Engine Optimization)." The core job is the same: figure out whether AI recommends you, and if not, why.
Otterly.ai tracks AI search visibility across multiple engines with scheduled monitoring. It works well for teams that want a dashboard they check weekly and strong trend tracking over time.
Profound focuses on understanding how AI perceives your brand through the lens of authority and entity recognition. Their approach leans into the content strategy side, helping you understand what to publish so AI models notice.
Be Recommended takes a snapshot approach: one report, 5 AI engines (ChatGPT, Claude, Perplexity, Gemini, Google AI Overviews), 50+ real prompts. You get a score from 0 to 100, a competitor comparison, and a prioritized action plan.
Where Otterly.ai and Profound have an edge
If you need ongoing monitoring with historical trend data, Otterly.ai has a mature dashboard for that. The subscription model suits teams that want to track movement week over week and respond to drops quickly.
Profound brings depth on entity analysis and content recommendations. That can be valuable for content teams with the bandwidth to execute a sustained publishing strategy based on AI perception signals.
Both have been in the market longer and have built communities around their respective approaches.
Where we built Be Recommended differently
We designed Be Recommended for a specific situation: you want to know your AI visibility score, understand the gaps, and get a clear action plan without committing to a monthly subscription before you know if the problem applies to you.
The one-time report model came from watching how startups and small agencies actually buy tools. Many don't need continuous monitoring yet. They need a baseline first. What is my score? Where do I rank against competitors? What should I fix first?
The 5-engine coverage was a deliberate choice. We found that brands visible on Perplexity were sometimes invisible on ChatGPT, and vice versa. Checking one engine gives you a partial picture. The 50+ prompt methodology uses the kind of queries real buyers type, not synthetic test queries, but prompts like "what is the best [category] for [use case]."
The output is a prioritized action plan, not just a number. Each recommendation maps to a specific engine and prompt cluster where the brand underperforms.
Which one fits your situation
Pick based on where you are:
You need ongoing dashboards and trend alerts. Otterly.ai is built for that. If your team reviews AI visibility weekly alongside SEO metrics, subscription monitoring makes sense.
You need deep content strategy guidance based on AI perception. Profound's entity analysis can inform a long-term content plan. Their approach works best when you have writers ready to act on the insights.
You need a baseline score and action plan without a subscription. That is the gap Be Recommended fills. Run one report, get the score across all 5 major AI engines, see where you stand against competitors, and work through the prioritized fixes.
At Inithouse, we built Be Recommended because the first question most brands ask is not "how has my AI visibility changed this month." It is "do AI models recommend me at all?" The score gives that answer in a single number. What comes after depends on the result.
You can run a report at berecommended.com.
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