I built a search engine for 700+ AI tools as a side project

Love that you're playing the long game here.
Anyone can just throw together a list of AI tools, but actually testing them out and sharing your real take is what keeps people coming back. In a space moving this crazy fast, having people's trust matters way more than just having the biggest list.

Position 15 in 2 weeks with no marketing budget is genuinely impressive. The hands on review angle is the right bet long term, nobody can fake "I actually paid for this." If I were you I would go all in on comparison queries, that is where the real search intent lives and where scrapers cannot compete.

The crawl requests are encouraging, but what caught my attention is the gap between Google's interest and user demand.

Search engines can validate that your content exists. They can't validate that you're solving the problem people are actually searching to solve. Closing that gap is probably more important than improving rankings at this stage.

The "I pay for every subscription I review" line is
what makes this credible. Most AI tool directories
are just scraped listings with affiliate links and
zero hands-on experience — you can tell nobody
actually used the tools. 270+ reviews where you
actually paid and tested is a real moat, because it's
the one thing competitors can't fake cheaply.

Being honest about "1 click" after 2 weeks is refreshing
too. Easy to only post the good numbers. The GSC
position of 15.3 and the crawl activity are the signals
that actually matter this early — Google noticing you
before humans do is the normal order for SEO-driven
products. The clicks follow once you climb past
position 10 on enough queries.

I'm building in a different space and going the
content/SEO route too, so watching this is useful.
Quick question on the search experience since you
asked — when someone types a task like "summarize
long PDFs," are you matching on the tool descriptions
you wrote, or on structured tags/categories behind
the scenes? Curious because task-based search lives
or dies on how well the intent maps to your data, and
that's the hard part.

Tried a couple searches — the comparison guides are
genuinely useful. The one thing I'd want is a quick
way to filter by "has a free tier" since that's usually
my first question before I even read the comparison.

the search experience is fine honestly, position 15.3 is why you have 1 click, not the UX. avg position 15 is page 2, and page 2 gets basically no clicks no matter how clean the page is. so your bottleneck is ranking, not the search box.

at this stage i'd stop spreading across 75 guides and pick the 5-8 already closest to page 1, then go deep to push those into the top 3. one guide ranking #3 for a query people actually type beats 75 sitting at 15. and skip the head terms like "best ai tools", those are owned by giant sites. your real moat is that you pay for and test every tool yourself, so the long-tail comparison queries ("X vs Y for [specific job]") are where your hands-on data ranks and nobody can fake it.

Awesome project! The AI tools space is getting crowded fast, so having a curated search engine is super valuable. I just launched a real-time analytics pipeline (FastAPI + TimescaleDB) on Product Hunt today — building in public is the way to go! The indexing approach you used sounds interesting. How are you handling freshness — do you periodically re-crawl or rely on submissions?

Love this. The fact you’re paying for and testing each tool is a huge trust signal.

Search feels solid; I’d love simple filters (pricing, free/paid, no-login). Also think your hands-on reviews are the real moat. Maybe highlight “personally tested” / “deep comparison” more prominently in the results.