Qlik Launches Qlik Answers: Enterprise AI Assistant Powered by Amazon Bedrock for Scalable Intelligence

Summary:Qlik has launched Qlik Answers, an enterprise-scale AI assistant built on Amazon Bedrock, designed to deliver trustworthy, sourced answers across structured and unstructured data for its over 40,000 customers globally. The system employs a layered, multi-agent architecture with cross-Region inference and Amazon Bedrock Guardrails to ensure compliance with data sovereignty requirements while providing reliable AI services. Since its general availability in February 2026, Qlik Answers has surfaced

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Qlik Launches Qlik Answers: Enterprise AI Assistant Powered by Amazon Bedrock

Qlik, a global leader in data integration, data quality, analytics, and AI, has launched Qlik Answers, an enterprise-scale AI assistant built on Amazon Bedrock. The system is designed to provide trustworthy, sourced answers across structured and unstructured data for its over 40,000 customers worldwide, helping them quickly access the information they need.

Key Challenges

Qlik faced three main challenges in developing Qlik Answers:

1. Orchestrating specialized reasoning without slowing down: Enterprise questions vary widely, from quick lookups to complex data analysis, and a general-purpose assistant struggles to meet all needs simultaneously.
2. Meeting data sovereignty requirements across regions: Qlik's customers span Europe, Asia Pacific, and the Americas, each with different expectations for data residency.
3. Forecasting model capacity ahead of demand: Qlik needed to plan token consumption and model availability 3-6 months ahead of major launches to ensure the product wouldn't strain under its own adoption.

Solution

Qlik Answers employs a layered architecture to address these challenges:

• Entry Layer: Provides a stable conversational entry point, allowing new backend capabilities to be added without changing the user interaction.
• Routing Layer: Quickly and accurately decides the path of the request without solving the task itself.
• Answer Layer: Coordinates response generation, choosing between a fast path for simple requests and a more deliberate path that breaks questions into sub-questions and pulls from multiple sources.
• Specialist Agent Layer: Defines how specialist agents, tools, state, and human-in-the-loop steps work, making it easier to add new specialists.
• Conversational Analytics Layer: Handles structured data questions by routing them to an app-aware reasoning path.
• Retrieval Layer: Runs unstructured document indexing and retrieval on Amazon OpenSearch Service, supporting knowledge base and document questions.
• Model Access Layer: Connects to Amazon Bedrock through Qlik's own LLM gateway for chat, streaming, embeddings, and reranking, and applies Amazon Bedrock Guardrails for content filtering and answer validation.

Technical Highlights

• Multi-model flexibility: Qlik can assign the best-suited model to each agent's task without locking the system to a single model's tradeoffs.
• Data sovereignty control: With Amazon Bedrock's cross-Region inference, Qlik can serve all 11 Regions while keeping data resident where compliance requires.
• Phased adoption of managed services: The AWS regional deployment model and capacity reservation options give Qlik room to scale and adopt services like Amazon Bedrock AgentCore without requiring a full migration.

Customer Impact

Since its launch in February 2026, Qlik Answers has surfaced more than 100,000 discoveries for customers and significantly boosted efficiency. For example:

• Lintech International: Indexed over 17,000 technical documents in Qlik Answers, reducing manual research time and speeding up response times by 75%, saving business managers up to 7 hours per week.
• Bystronic: Deployed an AI chatbot in 15 minutes, giving employees a way to query real-time operations data across departments.

Future Outlook

Qlik plans to continue expanding Qlik Answers' capabilities and evaluate Amazon Bedrock AgentCore for select workloads to reduce operational overhead while maintaining control over cost, latency, and portability. Additionally, Qlik is building a systematic framework for evaluating model performance to seamlessly switch to better-fit models as they become available.

Conclusion

Qlik Answers' adoption reflects the success of its architecture: fast where speed matters, deliberate where accuracy matters, grounded in real sources, and safe enough for regulated industries to depend on. Amazon Bedrock provided Qlik with the multi-model flexibility, data sovereignty control, and content filtering and validation capabilities needed to build a reliable AI experience at global scale.

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Source: AWS Machine Learning Blog (2026-10-07)

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Tags: #Qlik Follow #Amazon Bedrock Follow #Enterprise AI Follow #Multi-model Architecture Follow #Data Sovereignty Follow