ShownInAI

Buyers now ask AI which tools to buy before they ever open Google. We built ShownInAI so SaaS teams can see exactly when AI recommends them, when it recommends a competitor instead, and which sources to fix — starting with a free scan.

The "which sources put them there" part is the useful bit. Knowing you're missing from an answer doesn't help much; knowing it's because a competitor sits in three listicles and a G2 category does. Do you run each prompt several times? AI answers change a lot between runs, so a single scan can look better or worse than reality. Also curious if you support prompts in other languages. We work with Romanian businesses and the answers there look very different from English.

Really useful concept! AI search visibility is becoming increasingly important for SaaS brands as more buyers rely on AI tools for recommendations. I like the focus on competitor mentions and source-level insights, which can help marketers identify gaps and improve their visibility. 🚀

We see the same shift in public sector buying: people ask an assistant which suppliers to shortlist before they search. How do you choose the buyer prompts for a niche B2B category? Do you generate them from the product description, or can a team paste in the exact questions their customers ask? The second would help small markets, where generic prompts rarely name the product.

The idea of running real buyer prompts with web search turned on is a strong angle, because that is how many buyers now research SaaS tools. Showing which sources put competitors in the answer makes the report actionable instead of just a score. How often do the results change between runs, and do you recommend a re-check schedule to track progress after making fixes?

Nice focus on the sources, that's what makes it actionable. One thing I'd want as a marketer: can you tie visibility to results? For example, after a fix moves us into ChatGPT or Perplexity answers, do you show the change next to AI referral traffic in GA4? Is the gap different across assistants?

Seeing which sources put a competitor into the answer is the useful part. Two requests: a CSV export of cited source URLs per prompt, so a team can turn it straight into an outreach or listing plan. And a flag for whether the assistant actually searched the web or answered from training data, because the fix is very different in those two cases.

The 'who is named instead' angle is what makes this actionable — most tools stop at 'you are not mentioned'. Suggestion: show a before/after delta when a user fixes the sources you flag (e.g. 'named in 0 of N prompts, now 4 of N') — that closes the loop and proves the fix worked. Is a rescan comparison on the roadmap?

Checking whether AI assistants actually recommend your SaaS is a smart angle as search shifts to chatbots. Having it focused on visibility makes it easy to act on.

Checking whether AI assistants recommend a SaaS is a timely problem. Which engines does it query (ChatGPT, Perplexity, Gemini), and how often are results refreshed given how much the answers vary run to run?

The source-level breakdown is the part that stands out to me — knowing which pages AI assistants actually pull their recommendations from turns "why aren't we mentioned" into a fixable problem. I run a transcription tool and buyers increasingly ask AI for recommendations before searching, so this is exactly the report I'd want on my own category. Do the scans track visibility over time? Watching the trend move after publishing fixes would be the reason to check back weekly.

Showing which sources put a competitor into the AI answer is the useful part, since that tells you where to earn a mention. Do results vary much when the same prompt is run on different days? I'm curious how you handle that variance when reporting share of answers.