@emmaguetta · X

Claude code for GTM, connected to database signals and LinkedIn

u/ornymo_official · Reddit

how to reduce ai costs there are lots of way to reduce costs but there all complex to setup i know this cause i tried one in production so i built ornymo we cache meaning not the exact string allowing us to give same awnsers thus reducing llm costs and latency check it out at ornymo.com free for a limited time and let me know your feedback submitted by /u/ornymo_official to r/buildinpublic [link] [comments]

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

@m1mubeen · X

@trend_stack · X

@sahiinthehood · X

@meshlearningAI · X

u/sheshu29 · Reddit

My side project Hey everyone i have just created this website for developer who does not want to rely on ai agents so please visit and give me some feedback if you want any specific tools 🫠 submitted by /u/sheshu29 to r/SideProject [link] [comments]

apoorvumang · HN

TokenPath – token-level citations for LLM output, read from attention

@volosatovde · X

I’m building this to make it quicker and easier to find clients

@saim645 · X

@TraXx474387 · X

Built ZipSort 🗂️ Sort files inside ZIP archives in seconds — no upload, 100% client-side (your files never leave your browser). Set rules by extension, prefix, suffix or keyword → download a clean, organized ZIP. Free to try: