Qlik Answers Gains Traction as Enterprises Demand Explainable AI at Scale
Unlike many generative AI tools that stall at the proof-of-concept stage, Qlik Answers is proving effective in real-world environments.
Philadelphia/Bengaluru, August 23: Global data and AI leader Qlik has announced rising enterprise adoption of its decision-intelligence solution, Qlik Answers®, as organizations move from experimental AI pilots to mission-critical deployment across sectors like healthcare, manufacturing, and public services.
Unlike many generative AI tools that stall at the proof-of-concept stage, Qlik Answers is proving effective in real-world environments. Powered by Amazon Bedrock, it combines retrieval-augmented generation with enterprise indexing, enabling natural language queries on organizational data with explainable, sourced answers and actionable recommendations.
“Enterprises are rightly scrutinizing AI tools for practical value and reliability,” said Brendan Grady, EVP and GM of Qlik’s Analytics Business Unit. “With Qlik Answers, we’re seeing customers transition from experimentation to execution, using their own data assets to solve real problems today”.
Industry Deployments
- Bystronic, a global sheet-metal processor, built an AI chatbot in just 15 minutes, allowing employees to query real-time operations data across departments.
- Lintech International indexed 17,000+ technical documents, cutting manual research, accelerating response times by 75%, and freeing managers up to seven hours a week.
- TouchPoint Support Services, operating at 650 healthcare sites with plans to double, deployed Qlik Answers to provide rapid and compliant guidance to 15,000 frontline staff.
These examples underscore a shift from static dashboards to dynamic AI assistants, with Qlik positioning its solution as more than a chatbot — instead, as a governance-ready intelligence layer embedded into daily workflows.
As enterprises grapple with regulatory demands and operational complexity, Qlik Answers’ ability to connect structured and unstructured data while maintaining lineage and traceability is seen as a differentiator. The company says its growth signals that AI adoption in the enterprise is no longer about if, but how.
