启动 HN:Slashy(YC S25)——一个能够连接应用并执行任务的人工智能

11作者: hgaddipa001大约 14 小时前原帖
嗨,HN!我们是 Pranjali、Dhruv 和 Harsha,正在开发 Slashy(<a href="https:&#x2F;&#x2F;www.slashy.ai">https:&#x2F;&#x2F;www.slashy.ai</a>)。我们正在构建一个通用代理,能够连接到各种应用程序,读取其中的数据,并通过自定义工具、语义搜索和个性化记忆执行操作。这里有一个演示:<a href="https:&#x2F;&#x2F;www.youtube.com&#x2F;watch?v=OeApHMHhccA" rel="nofollow">https:&#x2F;&#x2F;www.youtube.com&#x2F;watch?v=OeApHMHhccA</a>。 在之前的创业项目中,我们意识到自己在应用程序中花费的时间更多是在做琐碎的工作,而不是实际构建产品。我们在抓取 LinkedIn 资料、更新电子表格、更新投资者报告以及在多个 Slack 渠道之间沟通上浪费了数百小时。我们的临界点出现在我查看屏幕使用时间时,发现自己每天在 Gmail 上花费了 4 个小时。我们决定,解决这个问题所创造的价值要远高于继续开发原来的创业项目(一个类似于 Lovable 的代码生成代理)。 Slashy 是一个 AI 代理,能够直接调用 Gmail、日历、Notion、电子表格等服务的工具。我们在内部构建了所有工具,因为我们发现大多数多通道平台(MCP)的质量较低,并增加了不必要的抽象层。通过这些工具,代理能够在您的应用程序中进行语义搜索,获取相关信息并执行操作(例如发送电子邮件、创建日历事件等)。这解决了在应用程序之间切换上下文和复制粘贴信息到 ChatGPT 的问题。 到目前为止,Slashy 已集成了 15 种不同的服务(G-Suite、Slack、Notion、Dropbox、Airtable、Outlook、电话、Linear、Hubspot 等)。我们使用单一代理架构(因为我们发现这可以减少幻觉),并使用我们自己的自定义工具——这样可以提高模型的质量,因为我们可以设计它们以适应通用代理结构,例如我们为 Slack/Notion 使用 markdown,而不是它们的本地文本结构。 那么,Slashy 与其他 100 个通用代理有什么不同呢? - 它真正采取行动:与仅提供信息的 ChatGPT 或 Claude 不同,Slashy 会研究公司,创建包含发现的 Google 文档,将联系人添加到您的 CRM,安排后续跟进,并发送个性化电子邮件——所有这些都在一个工作流程中完成。 - 跨工具上下文:大多数自动化工具在孤岛中工作(这是 MCP 最大的问题之一)。Slashy 理解您在不同平台上的数据。它可以读取您之前关于潜在客户的 Slack 对话,检查您的日历以确认可用性,在线研究他们的公司,并起草个性化电子邮件。支撑这一点的是我们自己的语义搜索功能。 - 用户行为图:我们的代理随着时间的推移,不仅记住过去的对话,还形成用户行为图,以了解基于先前用户对话所期望的操作。 - 无需技术设置:虽然 Zapier 需要构建复杂的流程并且常常默默失败,Slashy 通过自然语言工作。只需描述您想要自动化的内容。 - 自定义用户界面:对于我们的工具调用,我们为每个工具设计了自定义用户界面,以使用户体验更加自然。 以下是一些人们使用我们服务的工作流程示例: ▪ “每天查看我的日历,并给我发送一份关于我将要见的每个人的详细背景的 Notion 文档” ▪ “找到所有对我最新 LinkedIn 帖子做出反应的人的电子邮件,并发送个性化的外联” ▪ “你能帮我制作一份包含市场研究、竞争分析和财务预测的投资者推介文稿吗?” ▪ “进行完整的 Nvidia 折现现金流(DCF)分析” Slashy.ai 现已上线,提供免费套餐(每天 100 个积分),新账户还可获得 500 个积分。您可以立即尝试上述工作流程,我们为 HN 提供了一个特别代码(结账时输入 HACKERNEWS)。 希望大家和我们一样喜欢 Slashy :)
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Hi HN! – We’re Pranjali, Dhruv and Harsha, building Slashy (<a href="https:&#x2F;&#x2F;www.slashy.ai">https:&#x2F;&#x2F;www.slashy.ai</a>). We’re building a general agent that connects to apps and can read data across them and perform actions via custom tools, semantic search, and personalized memory. Here’s a demo: <a href="https:&#x2F;&#x2F;www.youtube.com&#x2F;watch?v=OeApHMHhccA" rel="nofollow">https:&#x2F;&#x2F;www.youtube.com&#x2F;watch?v=OeApHMHhccA</a>.<p>While working on a previous startup, we realized we were spending more time doing busywork in apps than actually building product. We lost hundreds of hours scraping LinkedIn profiles, updating spreadsheets, updating investor reports, and communicating across multiple Slack channels. Our breaking point happened after I checked my screen time and realized I spent 4 hours a day in Gmail. We decided that we could create more value solving this than by working on the original startup (a code generation agent similar to Lovable).<p>Slashy is an AI agent that uses direct tool calls to services such as Gmail, Calendar, Notion, Sheets and more. We built all of our tools in-house since we found that most MCPs are low quality and add an unnecessary layer of abstraction. Through these tools, the agent is able to semantically search across your apps, get relevant information, and perform actions (e.g. send emails, create calendar events, etc). This solves the problem of context-switching and copy-pasting information from an app back and forth into ChatGPT.<p>Slashy integrates to 15 different services so far (G-Suite, Slack, Notion, Dropbox, Airtable, Outlook, Phone, Linear, Hubspot, and more). We use a single agent architecture (as we found this reduces hallucinations), and use our own custom tools—doing so allows the model to have higher quality as we can design them to work in a general agent structure, for example we use markdown for Slack&#x2F;Notion instead of their native text structure.<p>So what makes Slashy different from the 100 other general agents?<p>- It Actually Takes Action: Unlike ChatGPT or Claude that just give you information, Slashy researches companies, creates Google Docs with findings, adds contacts to your CRM, schedules follow-ups, and sends personalized emails – all in one workflow.<p>- Cross-Tool Context: Most automation tools work in silos (one of the biggest problems with MCP). Slashy understands your data across platforms. It can read your previous Slack conversations about a prospect, check your calendar for availability, research their company online, and draft a personalized email. What powers this is our own semantic search functionality.<p>- User Action Graphs: Our agent over time has memory not just of past conversations, but also forms user actions graphs to know what actions are expected based on previous user conversations.<p>- No Technical Setup Required: While Zapier requires building complex flows and fails silently, Slashy works through natural language. Just describe what you want automated.<p>- Custom UI: For our tool calls we design custom UI for each of them to make the UX more natural.<p>Here are some examples of workflows people use us for:<p>▪ &quot;Every day look at my calendar and send me a notion doc with in-depth backgrounds on everyone I’m meeting&quot;<p>▪ &quot;Find the emails of everyone who reacted to my latest LinkedIn post and send personalized outreach&quot;<p>▪ &quot;Can you make me an investor pitch deck with market research, competitive analysis, and financial projections&quot;<p>▪ &quot;Doing a full Nvidia Discounted Cash Flow (DCF) analysis&quot;<p>Slashy.ai is live with a free tier (100 daily credits) along with 500 credits for any new account. You can immediately try out workflows like the ones above and we have a special code for HN (HACKERNEWS at checkout).<p>Hope you all enjoy Slashy as much as we do :)