RAG Search
beta
AI-powered enterprise search with RAG on QNAP NAS
Leverage AI-powered RAG to explore, understand, and generate insights from your stored content using natural language queries—unlocking deeper knowledge and discovery.
AI-enhanced enterprise search and knowledge management
Are you facing these challenges?
Overwhelming file volume and information overload? Finding the right document is time-consuming and complex.
Fragmented knowledge? Requires reviewing multiple files to grasp complete information.
Missed insights and inefficiencies: Traditional searches only retrieve information rather than understanding relationships between data.
Integrating RAG-based AI search technology not only enhances search accuracy and relevance but also plays a key role in optimizing search and analysis efficiency in enterprise search:
QNAP NAS pioneers RAG Search, transforming your NAS into an enterprise search powerhouse.
Qsirch is a powerful search engine designed exclusively for QNAP NAS. With Qsirch 5.6.0, it integrates cloud-based Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) technology. By incorporating AI-driven search, Qsirch enhances content comprehension and delivers more relevant results, transforming NAS into an advanced AI-powered enterprise search solution and knowledge management system for organizations, professionals, and individuals.
What can Qsirch RAG Search provide?
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Latest data
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Relevant insights
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Summarized information
Flexible and reliable enterprise search that simplifies knowledge management.
Choose your preferred LLM service provider and model, and activate it instantly with your API key. RAG Search supports
Google Gemini, OpenAI ChatGPT, Microsoft Azure OpenAI, and other OpenAI API compatible LLMs (such as DeepSeek and xAI Grok, etc.).
Select specific NAS folders for RAG Search. Only the most relevant content from the selected data, based on your search query, is sent to the cloud-based LLM for analysis, improving result accuracy while ensuring stronger data control.
RAG Search supports various document formats , including Word, Excel, PowerPoint, PDF, Email, and TXT, allowing you to search within specific formats. It delivers accurate answers and summaries, helping you quickly grasp key information and extract insights from large datasets.
RAG search not only provides critical information but also references to five relevant documents, empowering you to gain deeper insights from your data. Build a robust knowledge hub for future tracking, analysis, and application.
Real-time and multilingual knowledge retrieval
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Instant access to latest data
Ensures real-time search results even if NAS files are frequently updated.
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Multilingual AI search
Search and retrieves content in 23 languages, enabling seamless access to information across multilingual datasets.
Boost productivity with AI-powered search on QNAP NAS
Whether you are an enterprise managing vast documents, a professional handling extensive reports and internal data, or an organization seeking a fast AI-driven search solution with limited technical resources, Qsirch RAG Search delivers an efficient and intelligent knowledge management experience.
NAS system requirements for RAG Search
- Qsirch 5.6.0 (or later)
- 64-bit x86 and 64-bit ARM-based NAS
- QTS 5.0.1 (or later) or QuTS hero h5.0.1 (or later)
- Minimum 2GB RAM (4GB RAM recommended for optimum performance.)
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