Our product is deep and technical, so we needed answers that are genuinely correct and detailed, drawn from across all of our knowledge rather than just one place. Kapa delivers on that. It can answer using our docs, Confluence, Jira, and Slack together, it cites its sources, and it will say “I don’t know” instead of guessing. That level of accuracy is what gave us the confidence to put it in front of both our internal teams and our support team.

What I like best about kapa.ai is that it helps us meet customers in the moment with fast, relevant answers instead of sending them off to search across multiple places. In practice, that has made it easier for users to find guidance across docs, learning content, and support resources, and it has improved our workflow by making self-service more effective and more scalable.

We deployed kapa.ai as an AI Assistant on our API Developer Portal, Developer Dashboard, and in our Developer Community Slack. The setup was straightforward — kapa ingests your existing documentation, blog articles, support knowledge base articles, and a wide range of other technical sources to build a comprehensive knowledge base that powers instant, accurate answers to developer questions. What's been most impressive is how seamlessly it fits into the developer workflow. Rather than forcing users to hunt through multiple pages of documentation, the assistant surfaces the most relevant content in direct response to the specific question being asked — eliminating the friction of navigating to the right source. In addition to the powerful experience it adds to the front-end, kapa features a backend analytics dashboard that has been immensely insightful for our teams. The dashboard gives us a clear, real-time view into exactly what developers are asking, which sources are being used to answer those questions, and - critically - where the gaps are. That last piece is what's driven the most meaningful improvements to our documentation quality and coverage.