QNAP has launched RAG Search Beta, a feature in its Qsirch 5.6.0 search engine, harnessing cloud-based LLMs and Retrieval-Augmented Generation technology. This innovation aims to elevate traditional NAS server searches by enabling context-aware capabilities that facilitate better file retrieval, summarization of complex data, and informed decision-making. Users can customize searches across selected NAS folders and control which file formats are included. With support for various LLMs, the feature allows for a tailored search experience while ensuring accurate results that reflect the most current data.
QNAP's RAG Search Beta enhances NAS file search via cloud LLM integration, offering context-aware searches that improve data retrieval and decision-making.
By leveraging Retrieval-Augmented Generation, RAG Search not only elevates traditional search functions but also facilitates a deeper understanding of user intent.
Users can select which NAS folders to search and control which content gets uploaded, ensuring data sovereignty and enhancing search accuracy.
The flexibility to choose LLMs like OpenAI ChatGPT and Google Gemini allows users to tailor the AI search experience to their specific requirements.
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