@kashyap_ai · X

u/yonnnyy · Reddit

How should I revive my Saas after 300 hours spent developing To provide context, a couple months ago I created a pdf to JSON ai extraction engine. I know... There are hundreds of products like this but for me the value proposition is that other solutions were heavy weight, expensive, non intuitive templates, and was slow. Therefore I created my own and I met my goals. I see genuine value in my product but the lack of users says otherwise. I think my best option is to build on top of this

@0xLingjieKong · X

Hey @Sarakhan49309, I'm currently building an agent specialized in data analysis that reduces hallucinations. would love to connect!

@theprinceraj · X

Building for the tax professionals in India so they can work on things that matter and not waste time on repetitive tasks

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

u/wisesheets · Reddit

Most stock APIs are very expensive, have tons of data mistakes, and are not built for AI. Most stock APIs are expensive, have data mistakes, and are not designed for AI, so we built one. We recently launched the Wisesheets API and MCP server after repeatedly running into the same problems with financial data providers. Some APIs cost hundreds or thousands of dollars per month. Others have strict request limits and make it difficult to pull bulk data for screening or broader market analy

@pujaabharadwaj · X

@RunXItApp · X

u/Fun-Calendar8486 · Reddit

I am building yacdb.fyi, letting users ask natural-language questions about NFL data and turning them into queryable results. Yacdb.fyi goal is to allow users to construct questions about NFL data, think "Best 1st down conversion rate in 2025", and exposing a custom query layer on top (think SQL) allowing users to define their own queries to build data sets. They can chart in the app, using built in tooling, but can export the data as well if they want to use their own tooling. I am look

@helloo2012 · X

我不是程序员，但借助 ChatGPT 和 Codex，把微信读书里200多本书、笔记和阅读数据，做成了 以前只是一个模糊的想法，现在真的上线了。 AI对我最大的提效，不是少写几行代码，而是让我这种不会开发的人，也能把想法做出来

Doc2Md — 将 PDF、Word、Excel 等多种格式文件转换成 Agent 友好的 Markdown 格式 - [更多介绍](https://doc2md.cn)

@ernesto_lana · X