AI Agent features in Jitbit Helpdesk

Now with smarter, self-initiated Knowledge-base search and even external docs indexing

We've quietly rolled out a new AI-powered feature in Jitbit Helpdesk that brings our support automation closer to how modern AI coding assistants work - think Cursor, Windsurf, or GitHub Copilot, but for customer support.

Until now, our AI assist tools simply worked like enhanced autocomplete: when drafting a response to a customer, we'd preload the AI with relevant knowledge-base articles as "context", hoping it would incorporate that into its reply. Useful, but limiting. What if those articles weren't exactly relevant? What if something more precise existed elsewhere?

Now, our AI acts more like an Agent. It has access to a dedicated search tool - not just static context. When a support ticket comes in and a support rep hits the "GPT - Ticket response" button, the AI actively queries your Knowledge-base for relevant information on its own. If the first search isn't fruitful, it can refine its query and try again, iteratively. The process mimics how software engineers "vibe-code" with AI tools that fetch snippets and docs on demand from vectorized knowledge bases.

The search progress and results are displayed in the AI response box, so you can see the AI working on your behalf.

A key part of this setup: we don't just index your KB-articles, in Jitbit Helpdesk KB, but also your external documentation sites, blogs, and even entire public websites. All of this can be crawled and indexed into our vector database. Recursively. Again, the AI doesn't just look inside Jitbit Helpdesk KB articles you wrote - it can search any content you've pointed it to. But that's not all: it even searches the canned responses you saved in the app! And to be clear: all vector embeddings and data stay on our servers. We don't ship your vectors off to OpenAI, Gemini, Claude, or anywhere else. Our in-house infrastructure handles the vector search locally.

Here's how it works in practice:

1. You ask the AI to suggest a reply to a customer's question.

2. The AI calls the search tool with an initial query derived from the ticket.

3. It fetches relevant chunks from your Knowledge-base (and optionally your external docs/blogs).

4. If results are thin, it tweaks the query and searches again.

5. It drafts a response based on the best-matching content.

6. Importantly: we don't send this straight to the customer. The AI's suggested reply is shown to the support rep, who can edit, discard, or send it as-is.

This approach is already producing much sharper and context-aware drafts - especially for teams with sprawling documentation spread across multiple sources.

We didn't make a lot of noise about this feature when it shipped, but it's quietly becoming one of the more impactful AI upgrades in Jitbit Helpdesk to date.

If you're curious to wire up external docs into your KB search index, ping us - we'll show you how.

-- The Jitbit team

P.S. Available in the SaaS-version only