At this point there are multiple home RAG systems, pretty much using the same components, so does anyone know how this compares to others? I see that it imports GraphRAG which most other don’t
I can't speak for the internals, but I've found it to be dead simple to spin up locally and use, with decent results on the docs I've tested it with.
That said, I think a lot of AI chat services have recognized that document search is table stakes and are building this functionality into their tools, so I don't know whether Kotaemon as a standalone tool will be needed for much longer.
For example, my company was originally going to push out Kotaemon for private document search, but we have now put that on pause because we're exploring whether we can get the same results through our primary AI chat service, without having to point users to a separate tool.
> whether Kotaemon as a standalone tool will be needed for much longer.
I think a lot of AI startups will find themselves in this situation. Searching and summarizing docs is a no-brainer for OpenAI, Anthropic, etc. The only issue they have right now is that their models might not be reliable enough due to the non-deterministic nature of LLMs. In the long term, I believe Google, Amazon and Microsoft will probably be the big winners in this area since they can offer multiple models from major providers to de-risk things.
Unless AI complements an existing solution that is unique and/or is done well by existing businesses, it will be very difficult to compete.
