@kapiltaspa · X

@Enfo_Page · X

u/Akashrakshit77 · Reddit

I built a website generator that starts with Google reviews instead of a prompt Most AI website builders start by asking you to describe your business. I kept wondering why a local business should have to do that when its customers have already described what makes it worth choosing. So I built Presenvo. You paste a public Google Maps business listing, and it uses the listing details, photos, recurring review themes, and selected customer quotes to create a hosted website you can review

@localmama4u · X

@anefthynos · X

@localeadsite · X

LocaLead turns local business data into ready-to-contact leads with contact details, insights, and personalized AI outreach

@portraitmodeja · X

Helps web designers find businesses that need a new website instead of spending hours searching manually.

@goktugcinar · X

Interactive 3D globe to bid at your local city or at global scale. Social game to upvote your city!

@nopecode369 · X

This completely resonates. I actually poured my entire heart and passion into building for this exact reason. It’s designed as a dedicated home where real travelers, local guides, photographers, and trip planners can finally connect organically

@SudJourney · X

Working on this

kingchesco · HN

I know $90 for a dining app sounds absurd. And it’s not even an app; it's a wrapper for an LLM. But it is how it is built that makes it so expensive. I had to make a whole API just to call it (which because its own SAAS). All just to bypass dumb google reviews. Google Maps and reviews send people to places optimized for tourists and good copywriters. To find actual local hole-in-the-walls algorithmically, I had to first build that api (called BWENDI), a "spatial gravity" engine using 100GB+ of tweaked OSM, GeoNames, and other proprietary data. Instead of aggregating reviews, it mathematically calculates foot-traffic, throughput, transaction stats, and economic criticality among other factors. Bwendi is A Python/Node ETL pipeline feeding an LMDB-backed context API. It uses a proprietary 1MB binary grid served via Cloudflare Workers for millisecond edge reads with near-zero overhead, hosted in Switzerland. This was done of course to get the purest location context around every street

@businessHunter_ · X

Business Hunter scans Reddit, HN and GitHub for real demand signals → tells you exactly what to build before you write a line of code.