roguetink · Product Hunt

MonoCloud for Startups One identity layer for your customers, APIs, and agents

ent101 · HN

The Safe, Production-Ready Backend for AI-Generated Apps

@BrianHumphrie11 · X

做了一个 AI 中转站，分享给有需要的朋友： 我做这个站，打开就能用，需要时能稳定使用，日常工作和学习里能帮上一点忙。 自己平时 Token 用得比较多所以干脆搭了一个中转站。 希望大家可以更方便地使用 GPT、Claude 等 AI 能力，也能根据自己的需求了解 API 和 Token 方案。

@thread_snoop · X

Give you claude/codex free access to search through reddit :)

@jitendraballa · X

mohitprateek · HN

Anakin – API for your AI agents to access the most difficult websites

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

@happyendpointhq · X

@APIMart_ · X

APIMart 全新 UI 上线了。 新界面长什么样，看图👇 欢迎来 @chunxiangai 感谢赵纯想大哥帮忙设计的 UI，解决了一直 UI 特别丑的困扰 目前网站每天也达到了百万级的调用量，各方面都做了很多的努力，尽可能后面还能做的更好！

@SupportFixzi · X

Building an API monitoring tools which allows you to know when your AI breaks, before your users do. It has an API monitoring tool and an AI schema validator in it. This is a solution that can ensure your customers trust your app.

tahazsh · HN

Hi! I’m Taha. In many agentic products that support workflows (including one I worked on), I noticed they either don’t support node-based editors, or use React Flow and go through the difficult work of integrating it into their product to run it and work with their existing logic. So I thought about creating a tool that could help with this by closing the gap between the editor and the runtime. That’s why I created Wayflow. The basic architecture is simple: you just need to create a graph (which is a JSON object) that the runtime knows how to run. The runtime doesn’t care where that graph is coming from, it just needs the right schema. And with the help of the editor, you can create the graph, and then export it or directly save it on your backend in your database. And then when you want to execute it, you just hand it to the runtime. The runtime can either stream the execution (which is useful for the editor), or give you the final result. How you execute the graph is up to you: t

benjamin_jorgensen1 · Product Hunt

Constellation Gate AI Prompt injection and token savings - #1 in benchmarks