@MhdNihad921793 · X

Here Dubai realesta a new platform from end to end services

@polycontext · X

Context-aware localization for apps, games, and software.

@TajGervan · X

Hey Hassan, I am 18 and working on growth at olunix, I'd love to connect!

@japangor · X

I wanted FlightRadar24 for trains — no one was tracking Indian railways in real time, so I built it myself.

@atbigthumb · X

@Bizzzyapp · X

u/Apprehensive_Lock260 · Reddit

Made a simple UK postcode lookup app with AI insights - free to use Thought I'd try to build something for my portfolio and dabble with some AI integration too. Using deepseek, it analyses publicly available data from multiple government/free-to-use APIs. Data is available to browse separately of AI too. https://postcodecooker.com Things im still working on: - The calculation for the area score, sometimes feels to generous/harsh, hard to find a balance - The area circle on the map is

@fatwang2ai · X

做了一个 IP 检测工具： 开源。一次查询汇总 13 个数据源的风险评分、代理/机房类型和网络归属。不同平台的判断经常不一样，有些数据库甚至提供付费修正机制。与其只信某一家，不如把共识和差异放在一起看，更全面地了解你的 IP

@mutou1852 · X

做了一个中转站点收录网站，展示倍率、初始额度、可用分组和实测性能数据。 希望帮大家更快找到适合自己的站点。

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

@Gaurang_404 · X