Best Retrieval-Augmented Generation (RAG) Software for Swift

Find and compare the best Retrieval-Augmented Generation (RAG) software for Swift in 2025

Use the comparison tool below to compare the top Retrieval-Augmented Generation (RAG) software for Swift on the market. You can filter results by user reviews, pricing, features, platform, region, support options, integrations, and more.

  • 1
    Klee Reviews
    Experience the power of localized and secure AI right on your desktop, providing you with in-depth insights while maintaining complete data security and privacy. Our innovative macOS-native application combines efficiency, privacy, and intelligence through its state-of-the-art AI functionalities. The RAG system is capable of tapping into data from a local knowledge base to enhance the capabilities of the large language model (LLM), allowing you to keep sensitive information on-site while improving the quality of responses generated by the model. To set up RAG locally, you begin by breaking down documents into smaller segments, encoding these segments into vectors, and storing them in a vector database for future use. This vectorized information will play a crucial role during retrieval operations. When a user submits a query, the system fetches the most pertinent segments from the local knowledge base, combining them with the original query to formulate an accurate response using the LLM. Additionally, we are pleased to offer individual users lifetime free access to our application. By prioritizing user privacy and data security, our solution stands out in a crowded market.
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