What challenges did you face when building your own RAG system?

https://brixxs.com/faq/what-challenge...

In this video, we delve into the challenges of building a custom Retrieval-Augmented Generation (RAG) system, likening the journey to expecting a big finish but only getting modest results. We discuss the extended development timelines, often longer than anticipated, due to the complexities of AI model training and integration. Another major challenge is the rapid pace of technological change, where new advancements can quickly outdate custom-built systems.

We explore the integration difficulties similar to fitting a square peg into a round hole, dealing with API management complications and ensuring seamless system integration. To tackle these issues, we suggest adopting platform-based approaches or leveraging preconfigured solutions to ease the development process and speed up deployment. Businesses are encouraged to stay updated with technological trends, adopt scalable and flexible solutions, and plan carefully to overcome potential challenges for successful system integrations.

For those looking for alternatives, we look into prebuilt solutions or no-code and low-code platforms as efficient means for AI integration. Join us as we unpack these strategies and provide insights into navigating the RAG system development landscape.

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