
Valendata | Automate Web Data Extraction & Browser Skills
Transform the web into your own API. Valendata automates web data extraction from browser automation to structured APIs with zero maintenance. Trusted by 100+ data teams.
@valy_data · X
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Transform the web into your own API. Valendata automates web data extraction from browser automation to structured APIs with zero maintenance. Trusted by 100+ data teams.
@valy_data · X

为 CSV、Excel、JSON 和 Parquet 文件创建可视化数据 ETL 管道。
@ashkans_dev · X
An ETL tool:

Describe a dashboard and Vetros builds it on your real data — sources connected, data modeled, every number traceable, kept up to date for you. The data product builder for teams w
@AzuolasEnd · X

从 PDF 自动提取结构化数据,用于工作流自动化。
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

用实时市场数据和AI投资助手模拟和分析投资组合。
u/Substantial_Net_1677 · Reddit
I will try once again A few weeks ago I posted here asking for feedback on a portfolio analysis tool I was building. The idea is simple: before buying or selling anything, I wanted a way to simulate changes to my portfolio and actually understand the impact instead of relying on gut feeling. So I built S-Markets . Some of the things it does: Simulate "what if" scenarios before making changes. Analyze diversification and concentration. Explain portfolio risks in plain English wi

分析500万+移动应用的变现策略和广告投放方式。
@axel_driowya · X
sure! lets connect! im Building — mapping out untamed market gaps & profitable niches. Publishing 1 free niche every day Documenting the build

用AI分析敏感数据,通过客户端加密实现端到端保护。
@JackiePeters · X

AI驱动虚拟数据室,帮助交易团队将散乱文档转化为引导性体验。
@Puneeeeeeet · X
We help brands go viral on X with organic video campaigns that people actually want to watch. wanna try for

自动化B2B收入执行,统一营销、销售和客户数据。
@k_mansourizadeh · X
Curious to learn more, building

试试这个高性能的 React 数据网格组件,已针对企业使用优化。
@leethatengineer · X
Building LyteNyte Grid

文档解析 API,准确提取表格、公式和结构化数据给 AI 代理。
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
