Press Release: QNAP® Systems, Inc., a leading innovator in computing, networking, and storage solutions, introduces RAG Search Beta, a groundbreaking feature in Qsirch 5.6.0, a powerful NAS search engine with artificial intelligence. By integrating public cloudWith the LLM (Large Language Model) and RAG (Retrieval-Augmented Generation) technology, QNAP is a pioneer in implementing RAG search functions within NAS as a private cloudua provides highly accurate, contextual and AI-powered knowledge retrieval that goes beyond traditional file and image search. RAG Search transforms QNAP NAS into an advanced AI-driven knowledge center, enabling enterprises, professionals, and individuals to streamline information retrieval while ensuring data sovereignty.
“As enterprises create and store ever-increasing amounts of data, the demand for efficient, intelligent, and secure search solutions has never been greater,” said Amol Narkhede, Director of QNAP’s SaaS Backup and Data Management BU. “With the RAG search feature in the app, we integrate advanced AI-powered search solutions directly into QNAP NAS, enabling users to perform intuitive and understandable data analysis and search. RAG search gives enterprises greater flexibility and control over data search, allowing for customized searches and selection of the most suitable LLM service, greatly improving the efficiency and accuracy of knowledge search.”
Main RAG search functions
- Contextual search powered by artificial intelligence
It recognizes user intent and tailors queries to provide accurate and relevant results, enabling professionals to search files, retrieve information, summarize complex data, and make informed decisions. - Customizable LLM selection
Powered by OpenAI ChatGPT, Google Gemini, Microsoft Azure OpenAI, and other OpenAI API-compatible LLM models (such as DeepSeek or xAi Grok), enabling flexible integration of AI-powered search. - Customized data search scope
Select specific NAS folders to search and the RAG search service will upload to cloudOnly the most relevant content is included in the LLM analysis, increasing accuracy and strengthening data control. - Customizable file formats on request
Supports various file formats, including Word, Excel, PowerPoint, PDF, TXT and email (.eml). Users select specific formats for search and analysis based on their needs, enabling seamless knowledge retrieval across multiple document formats. - Traceable insights
You can link to up to five relevant documents in your search results, which increases data validity and deepens your analysis. - Real-time knowledge search
Search results reflect the latest versions of files on the NAS and provide accurate and up-to-date information. - Multilingual document analysis
Search and retrieve content in 23 languages, enabling seamless access to information in multilingual datasets.
More information about RAG searches Beta in Qsirch 5.6.0 you can find at https://www.qnap.com/go/solution/rag-ai-search/.
