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By leveraging Retrieval Augmented Generation technology, Qlik Answers combines retrieval-based and generative AI methods to deliver precise and contextually relevant responses
Qlik, a prominent player in data integration, analytics, and AI, has announced the general availability of Qlik Answers, a new self-service AI solution designed to help businesses extract actionable insights from vast amounts of unstructured data.
Qlik Answers integrates generative AI with Qlik’s established data analytics capabilities, addressing a significant challenge in enterprise AI adoption—explainability. This innovative solution ensures that AI-generated results are fully transparent, with clear links to their source documents, which is vital for building trust and consistency in AI-driven decisions. By leveraging Retrieval Augmented Generation (RAG) technology, Qlik Answers combines retrieval-based and generative AI methods to deliver precise and contextually relevant responses. This approach enables the solution to pull from extensive knowledge bases, synthesize information, and provide users with actionable answers that directly impact business outcomes. The solution is designed for seamless integration into existing Qlik business intelligence workflows, minimizing deployment time and complexity while avoiding technical debt. Key features include AI-powered responses, rapid deployment, and broad connectivity with Qlik’s enterprise connectors, and enhanced efficiency in real-time decision-making.
Brendan Grady, Executive Vice President and General Manager of Qlik's Analytics Business Unit, stated that Qlik Answers is designed to help businesses leverage their unstructured data for improved decision-making. He emphasized that by integrating Qlik's analytics capabilities with generative AI, the solution provides a tool that effectively translates unstructured data into tangible business outcomes. With Qlik Answers, enterprises can unlock the full potential of their unstructured data, driving more informed and efficient business decisions.
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