@f_lecroissant · X

building apps for business on

@RohanMuni · X

mat10112 · HN

Memsprout – share your AI context with teammates

@vlipadev · X

u/albanianspy · Reddit

the boring internal tool became the product we didn’t start with a saas idea. we were just annoyed that every agent-built UI looked weirdly related. so we made an internal finish gate: real screen references, a design contract, browser checks, and a ban list for generic AI defaults. one developer kept asking why it wasn’t public. eventually we stopped having a good answer. now UIZZE has a few paid users. builder disclosure: it’s mine, $9/mo or $99 lifetime: https://uizze.com current

@TharejaRushil · X

zaczuo · Product Hunt

Athena by Shoplazza An orchestrator agent for your entire commerce stack

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/Forsaken_Coconut3717 · Reddit

Anyone down to test each other's tools? (socks stay on) Hey all! I've been a lurker for a number of years and I think it's finally time for me. I built a tool that I think might actually be worth something! At its core it basically unifies every customer’s texts and emails into one shared conversation and is built for setting up AI agents to run your communications right from within the platform. It has a lot of moving parts but I think it can genuinely be the next big platform for man

@ForgeLab_Brain · X

Open beta launched. See more here: 🌐 #VibeCoding #BuildInPublic #IndieHacker #AIdev

zxhywork · V2EX

Muse Image AI Meta Superintelligence Labs 7 月 7 号发布了他们第一个图像模型 Muse Image ，内部代号 Mango 。玩了两天，这个模型有几个点确实有意思： - **Agentic 生成**：出图前先规划布局，需要事实的场景会联网搜，画完自查一轮再交稿，长 prompt 一次过的概率明显高 - **图内文字能看了**：海报标题、图表、甚至可扫的二维码都能直接画进图里，这是大部分生图模型至今糊掉的地方 - **多参考图合成**：从几张照片里分别取人脸、服装、产品、背景，融成一张不违和的图 官方入口在 Meta AI App / meta.ai / Instagram Stories ，国内用着别扭，还得装 App 。我就照着上一个站的路子做了个纯网页版：[museimages.io]( https://museimages.io/)。 产品上砍得很狠，只做图像，三个入口： - [Meta Muse Image 在线生成器]( https://museimages.io/ai-image-generator)

@hisachinj · X