Show HN: 一个学习你产品的 AI 助手,为你的用户提供指引
12 分•作者: pancomplex•5 个月前
嘿,HN!我是 Christian,是 <a href="https://frigade.ai">https://frigade.ai</a> 的联合创始人。我们构建了一个强大的 AI 智能体,它可以自动学习如何使用任何基于网络的应用程序,进而直接在用户界面中引导用户,自动生成文档,甚至代表用户采取行动。你可以把它想象成旧版 MS Office 里的 Clippy,但功能更强大,而且真的很有用。<p>你可以在这里看到智能体和工具调用 SDK 的实际应用:<a href="https://www.youtube.com/watch?v=UPe0t3A1Vpg" rel="nofollow">https://www.youtube.com/watch?v=UPe0t3A1Vpg</a><p>这与其他的 AI 客户支持产品有什么不同?<p>大多数 AI “副驾驶” 实际上只是被美化了的聊天机器人。它们会浏览你的帮助中心,然后吐出一些不具体的要点。基本上就是希望用户自己搞清楚。最终,这把负担推给了用户。而且,它还假设公司会随着产品的每一次变化而更新它们的帮助中心。这意味着需要不断截取新产品 UI 或功能的屏幕截图,以提供准确的说明。这些解决方案只利用了 AI 潜力的很小一部分,而 AI 现在可以对软件界面进行广泛的推理。<p>使用 Frigade AI,我们直接在产品中引导用户,并根据当前用户的状态和上下文构建按需导览。智能体还可以直接代表用户采取行动,例如邀请同事加入工作区或检索账单信息(通过我们的工具调用 SDK)。<p>这一切直到最近才成为可能。最新的前沿模型(GPT 4.1、Claude 4、Gemini 2.5 等)能够以 6 个月前根本无法实现的方式来推理 UI 和工作流程。这就是为什么我们如此兴奋地将这项技术带到尚未启用 AI 的复杂遗留 SaaS 应用程序的前沿。<p>它是如何工作的?<p>1. 邀请 agent@frigade.ai 加入你的产品。你可以根据不同的角色发送多个邀请。<p>2. 我们的智能体会自动探索并推理你的应用程序。<p>3. 附加任何现有的帮助中心资源或培训文档,以补充智能体的理解。完全可选。<p>4. 安装智能体助手 Javascript 代码片段(只需几行)。<p>5. 就这样。你的用户现在就可以开始提问,并实时获得按需产品导览和解答,而无需任何额外开销。<p>这个过程只需几分钟。一旦运行,你可以通过对智能体提供的回复进行评分和提供反馈来改进它。如果你想进一步集成,你还可以将自己的代码连接到我们的工具调用 SDK,以使智能体能够直接查找客户信息、发放退款等。只需用几行代码描述工具及其参数,用自然语言描述,并传递一个 Javascript promise(例如,进行 API 调用,调用应用程序中的一个函数等),即可完成这些调用。<p>很想听听 HN 社区对这种方法的看法!你是在从头开始构建自己的 AI 智能体,还是想嵌入一个现成的智能体?
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Hey HN! My name is Christian, and I’m the co-founder of <a href="https://frigade.ai">https://frigade.ai</a>. We’ve built a powerful AI agent that automatically learns how to use any web-based product, and in turn guides users directly in the UI, automatically generates documentation, and even takes actions on a user’s behalf. Think of it as Clippy from the old MS Office. But on steroids. And actually helpful.<p>You can see the agent and tool-calling SDK in action here: <a href="https://www.youtube.com/watch?v=UPe0t3A1Vpg" rel="nofollow">https://www.youtube.com/watch?v=UPe0t3A1Vpg</a><p>How is this different from other AI customer support products?<p>Most AI "copilots" are really just glorified chatbots. They skim your help center and spit out some nonspecific bullet points. Basically some ‘hopes and prayers’ that your users will figure it out. Ultimately, this puts the burden on the user to follow through. And assumes companies are keeping their help center up-to-date with every product change. That means constant screenshots of new product UI or features for accurate instructions.These solutions leverage only a fraction of what’s possible with AI, which can now reason about software interfaces extensively.<p>With Frigade AI, we guide the user directly in the product and build on-demand tours based on the current user’s state and context. The agents can also take actions immediately on a user’s behalf, e.g. inviting a colleague to a workspace or retrieving billing information (via our tool calling SDK).<p>This was only made possible recently. The latest frontier models (GPT 4.1, Claude 4, Gemini 2.5, etc.) are able to reason about UIs and workflows in a way that simply didn’t work just 6 months ago. That’s why we’re so excited to bring this technology to the forefront of complex legacy SaaS applications that are not yet AI enabled.<p>How does it work?<p>1. Invite agent@frigade.ai to your product. You can send multiple invitations based on distinct roles.<p>2. Our agent automatically explores and reasons about your application.<p>3. Attach any existing help center resources or training documentation to supplement the agent’s understanding. Totally optional.<p>4. Install the agent assistant Javascript snippet (just a few lines).<p>5. That’s it. Your users can now start asking questions and get on demand product tours and questions answered in real time without any overhead.<p>This process takes only a few minutes. Once running, you can improve the agent by rating and providing feedback to the responses it provides. If you want to integrate further, you can also hook up your own code to our tool calling SDK to enable the agent to look up customer info, issue refunds, etc. directly. These calls can be made with just a few lines of code by describing the tool and its parameters in natural language and passing a single Javascript promise (e.g. make an API call, call a function in your app, etc.).<p>Would love to hear what the HN crowd thinks about this approach! Are you building your own AI agent from scratch, or looking to embed one off the shelf?