Building RAG-based LLM Applications with DataStax and Fiddler

Retrieval augmented generation (RAG) is an efficient deployment method for enterprises to launch large language model (LLM) applications. RAG enables AI teams to build applications on top of existing open-source LLMs or those provided by companies like OpenAI, Cohere, or Anthropic. This approach allows the introduction of time-sensitive and private information not possible with foundation models alone. DataStax Astra DB and Fiddler's AI Observability platform have partnered to enable enterprises and startups to quickly put accurate RAG applications into production. The partnership combines Astra DB's real-time vector capabilities for building generative AI applications with Fiddler's monitoring capabilities, addressing safety, accuracy, and control requirements for deploying RAG applications in production.