pro_methe5 · HN

I scrape an $8.5M-ARR company run by AI agents and chart it live

@RasinMuhammedX · X

Declarative Synthetic Data Generation.

@timnuss · X

Trust layer for agriculture

@ItsPavanGK · X

Built for Indian Staffing Vendors. By Operators. Vendordesk platform helps staffing vendors manage their complete hiring lifecycle — candidate pipeline, AI-powered resume screening, timesheet billing, client management, and sub-vendor operations.

@franciscobuilds · X

1. Building Tabkeel, an AI-powered analytics platform for SaaS products 2. For founders and teams who want to actually understand and act on their data 3.

@marcin_u2 · X

-> here it is! claude finally knows everything gpt knows. and both of them know everything that's happened across your email, drive, slack, notion, github and granola :)

g418572664 · V2EX

做了一个文档解析与记忆工具，专门辅助给传统行业做 AI 落地的老哥 现在 AI+的工作还挺常见的，就像大佬们说的，“所有行业的产品可能都会用 AI 重新做一遍”。最常见的就是各种 agent ，说要用 AI 赋能传统行业啥的，代替人类专家去处理海量的复杂资料、进行深度分析并做出决策。 举个例子，金融行业的“智能审计与尽调 Agent”。 过去，银行或投资机构想要给一家企业贷款或投资，需要人类审计师去读几十份、每份几百页的招股书和财务报表。现在虽然有了 AI ，但把文件一股脑全丢给它是不现实的，且不说烧 token 的问题，这些文档里有无数的跨行、跨列单元格表格，普通工具一拉，表格数据全串行了。如果 AI 把“第一季度利润”和“第二季度支出”的信息碎在一块，那得出的财务分析就完蛋了。 所以，现在要真想开发出一个能干活，还确保正确率的 agent ，就需要一个专业的、AI-native 的解析工具，把复杂的表结构和章节层级完整还原出来。我做的工具 Knowhere 就是干这个的： https://knowhereto.ai/?utm_source=v2ex 它能把复

@matthew_meadows · X

Correlation Studio - Discovery Mining • Causation Analysis A powerful new SaaS statistics application that brings the insights of correlation data science to everyone. Data science without the code.