The Kapa.ai team has been a strong partner, consistently supporting our goals throughout our journey. Whenever we had technical questions, their technical leaders were readily available to help us. The platform itself is fast, easy to implement, and keeps our information up to date across nearly a dozen different sources. Having Kapa allowed us to move quickly, first by introducing their widget to validate customer demand and value, and then by enabling us to focus on the problems we were solving without having to allocate engineering resources to knowledge-base RAG infrastructure. Additionally, seeing examples of their customers in the wild, such as Amplitude, showed us what Kapa is capable of and helped us during our planning phase. This has been valuable as we transitioned to utilizing their retrieval API to feed accurate context directly into our user-facing documentation agent. Review collected by and hosted on G2.com.

Because our setup is focused almost entirely on the retrieval API—with our use of the widget soon phasing out—we only utilize a fraction of Kapa's broader feature set, though the costs largely remain the same. We also have not yet fully validated its multilingual performance at scale compared to English, which is an important consideration for us. Lastly, while the platform allowed us to move quickly and avoid building custom documentation RAG infrastructure internally, its long-term value proposition might shift as we choose where to focus our internal AI resources. Since our internal R&D is heavily dedicated to core product data innovations, using a third-party tool for technical documentation context makes sense for now, but I look forward to what Kapa releases over the next 12 months to see how those features will further support our long-term focus. Review collected by and hosted on G2.com.