AISEOScan

While others focus on old-school SEO, we realized AI engines like ChatGPT, Perplexity, and Claude are becoming the new “search front page.” The idea was simple: help websites get cited by AI, not just indexed by Google.

We started by scanning our own projects and noticed huge gaps between traditional SEO scores and what AI engines actually picked up. Early testers confirmed the same pain point: their sites ranked fine in Google, but weren’t showing up in AI answers. That’s when we knew the product had real demand.

I built the solution solo, using a stack that includes Next.js 14 for the frontend, Supabase for database , Stripe for payments, Vercel KV for caching, and supporting libraries such as Axios, jsPDF, nanoid/uuid, and lucide-react. One of the key challenges was ensuring the product remained lightweight, privacy-friendly, and reliable, while still managing critical features like secure payments and automated PDF report generation. As a solo founder, I also had to carefully balance development speed with scalability. Overall, the process was a great learning experience and helped me design a system that is both efficient and sustainable.

We shared the tool in indie maker spaces, SEO communities, and with early-stage founders. The message resonated: “Is your site ready for AI search?” From there, word-of-mouth and organic interest drove steady growth without heavy ads.

Building for the future of search means educating people as much as offering a tool. Many don’t realize AI engines work differently from Google. The biggest lesson? Keep it simple, actionable, and fast, because founders want clarity, not another overwhelming SEO report.