
Vela | Grounded, No-Code AI Customer Support Agent
从你的文档和Notion学习的AI客服代理,自动处理客户支持。
@vela_cx · X
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从你的文档和Notion学习的AI客服代理,自动处理客户支持。
@vela_cx · X

从中央知识库生成文档、帮助中心、聊天机器人和AI搜索工具。
u/Glittering_Stage4118 · Reddit
Building a company brain that can host any interface I’ve always felt like company knowledge is way too fragmented. Docs live in one place, support answers in another, marketing content somewhere else, and internal know-how is usually buried across tools, Slack threads, and old pages. Even when companies have the knowledge, turning it into the right interface for the right audience is still way too hard. I’ve been building Sophic to solve exactly that. At its core, Sophic


检测您的写作中的AI内容,修改后重新扫描验证更改。
u/Cnye36 · Reddit
I built an AI detector and I'm not sure the score is the useful part I started building DidAIwriteit.com thinking the most useful part was the sentence level scoring and rescan. I thought, scan a draft, flag suspicious sentences, help the user rewrite and rescan to pass the detector before a teacher, client, or editor did. That felt like the product. But I kept running back into the same question: What does that actually prove, at the end of the day it is still just a number, the landsca

自主AI研究引擎,根据提示词生成带真实引用的完整学术论文。
@fedeponte1 · X
my first saas. i think i built something people actually want and completely failed at the business side. would genuinely love help. openpaper ( writes full, cited research papers from a prompt. research, outline, writing, real citations, export. the honest numbers: - ~2,300 signups - ~1,500 generated a full paper. people actually use it. - ~5 have ever paid. ~$45/mo. activation is great, revenue is basically zero. i've been staring at this for weeks. the paywall is on export (pay ~$12 to download the pdf). but the full cited paper is right there on screen, free, you can read it and copy-paste it. so i'm charging for the gift wrap after handing over the gift. almost nobody even reaches checkout. 76% generate exactly one paper and leave. one-and-done, so subscriptions make no sense. the audience is mostly students and researchers on personal gmail, all over the world, almost none on university or company emails. traffic is x and github. so i genuinely can't tell

为 AI 代理的表单提交后端服务。
@gonelf · X
So many things - dead simple way to share projects within your team - dead simple base - no backend forms - ez directory submissions - a Lego event

每日阅读AI精选新闻摘要,关注全球发展。
@ChenglongW98225 · X
做了一个AI新闻日报,感兴趣的可以点下方链接看一下 有什么需要改进的也可以直接评论我,我都会认真回复

按职业场景语义搜索 AI Skills,保存收藏集,一键装入 Claude Code。
SkillForge — Claude Skill 发现与分发平台,按职业场景组织 5700+ skill 覆盖 30 个垂直领域,一行命令装到 Claude Code / Cursor,登录后可留存自己的工具集

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