Feel free to drop your email if you’re interested!<p>For context: As we talked with developers and product builders we noticed a common need for customising LLMs on their own data through fine-tuning (Retrieval Augmented Generation mainly, but some-times actual fine-tuning). Models like GPT, Claude and Llama2 have great reasoning capabilities but may not perform optimally for specific use cases where relevant information from knowledge sources is needed.<p>As we looked how this is done today it requires mastering a bunch of things from data retrieval, configuring vector DBs, data enrichement using embedding and ensuring things work not only for a few documents but for large amounts of data.<p>We're building ragapi to manage all this heavy lifting so you can focus on building the rest of the (i.e use case related things).