Anyone else taking a similar approach?

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And we haven't really seen security or privacy issues in terms of competitor leakage. There is more concern around customer data and privacy, and in that regard, we invest heavily in security and have safeguards to help minimize the risk of any customer data issues.

You can see the agent and tool-calling SDK in action here: https://www.youtube.com/watch?v=UPe0t3A1Vpg

How is this different from other AI customer support products?

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.

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).

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.

How does it work?

1. Invite agent@frigade.ai to your product. You can send multiple invitations based on distinct roles.

2. Our agent automatically explores and reasons about your application.

3. Attach any existing help center resources or training documentation to supplement the agent’s understanding. Totally optional.

4. Install the agent assistant Javascript snippet (just a few lines).

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.

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.).

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?

Comments URL: https://news.ycombinator.com/item?id=44733892

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