See where your brand is discovered and fix what blocks it
Your brand is being discovered in more places than search, but you cannot see where you are missing. Rankings, crawls, content, and links live in separate tools, leaving teams guessing what to fix first. SEORCE gives one clear view of discovery across search and AI, shows what is blocking visibility, who is winning instead, and what to fix first. One system to understand, prioritize, and act without scattered dashboards.
Love the concept and the AI ranking!
This is a timely and much needed product as AI driven discovery becomes a primary channel for brand visibility. Tracking presence across ChatGPT, Claude, Perplexity, Gemini, and AI Overviews addresses a gap most teams are currently blind to. From a technical standpoint, how are you detecting and normalizing brand mentions across different model responses and update cycles while keeping the insights comparable in real time?
I’ve been searching for products like this for some time. It looks solid. I’ll test it out and see if I can track its progress going forward.
Oh man, I'm so wanting this for apps! This is a pain I have, but these days I feel it mainly in my mobile projects ( " for ASO instead of SEO" ) . Is this something you guys are thinking about? Anyway... really interesting project. Congrats!
Hey @kulraj how are you doing today? I've been on your website and wanted to share a thought. The product itself makes sense, but on the website it is a little hard to immediately understand what the primary action is. You have a few CTAs that could all serve a different purpose. What would you like your users to do first ideally? I can share a few ideas on how to make it better if you are interested. Either way, nice work on the product.
A measure of community engagement at launch. Higher means more people noticed and interacted with the product. It's a traction signal, not a quality rating.
Discussion threads divided by interest score. Above 0.30 is strong. Below 0.15 suggests the product got clicks but not conversation.
Categories come from the product's launch tags. Most products appear in 2-3 categories. The primary category is listed first.
The scores reflect launch-period engagement. Historical data is preserved and doesn't change retroactively. The build date at the bottom shows when the index was last refreshed.