Sana Khan

A year ago, half the marketing world told us "AI search" was overhyped. The other half was shipping "ChatGPT SEO checklists" in a week.

We ignored both.

Instead we did one boring thing: we scraped LLM citations. Every day. Across ChatGPT, Perplexity, Gemini, Claude. For hundreds of brands. And we asked one question when AI recommends a product, where does that recommendation actually come from?

Here's what we found that nobody was talking about:

I said "never again" to hardware.

I meant it. I had done it before. I know what hardware costs, not just in money, but in decisions you make at 2am about components that may or may not arrive, about inventory that ties up capital for months before a single unit ships. When I moved into SaaS, the relief was real. Software scales. Software does not sit in a warehouse. 

Hey ProductHunt!

Trophy is now powering over 24M streaks which is kind of crazy to think about considering we only launched 1.0 here in January this year.
One of the parts I find most interesting about building horizontal infrastructure is that as you scale and power more and more products you get to see insights that most teams building in isolation will only see a part of, and you can use those insights to make the the infrastructure better for everyone.
For example, because we power streaks for so many users, Trophy can tell that 25% of all streaks are lost on a Friday, closely followed by Saturday (19%) and then Wednesday (18%).