What you need to know about RAG to build better AI apps

Enterprise AppGen introduces an AI-powered app generation platform that leverages retrieval-augmented generation (RAG) to enhance the capabilities of large language models (LLMs) by integrating domain-specific and current information into their responses. While LLMs like ChatGPT and Claude are adept generalists, they often lack the nuanced, up-to-date knowledge needed for specific applications. RAG addresses this by using a combination of vector databases and similarity searches to incorporate relevant, specialized data without the need for model fine-tuning. This approach is particularly beneficial for domain-specific applications in fields like healthcare, finance, and legal services, where precise and context-aware responses are crucial. However, the additional retrieval step in RAG can result in latency, which may not suit real-time applications. Retool facilitates the creation of RAG-powered applications by providing user-friendly tools for processing and storing vectors, thus enabling teams to build AI solutions tailored to their needs.