@localmama4u · X

@portraitmodeja · X

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

@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

@KSertttttttt · X

Tovo - AI 会议/面试助手 — 在会议中，Tovo 是一款注重隐私的 AI 助手，完全在您的设备上运行，为会议和对话提供实时转录和智能协助，无需向外部服务器发送任何数据。

@cultkoushik · X

A problem warehouse for creators

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

ldenoue · HN

Show HN: PDF reflow in the browser with local AI model

@fortsignal1 · X

@ArnavGupta47851 · X

Vibe coding is fun. Sharing what you built is not. So I built unlocalhost. Tell your coding agent to deploy, say who is allowed in, and you get a real link with a login wall already in front of it.

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

@WingBeerSpecial · X

- Discover daily specials at restaurants near you. Currently limited to Ontario Canada. Let us know if you like to concept and want to see coverage in your area next!