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# How Qlik built grounded, enterprise-scale AI with Amazon Bedrock
- URL: https://www.stirup.si/how-qlik-built-grounded-enterprise-scale-ai-with-amazon-bedrock/
- Published: 2026-10-11T14:43:34.000Z
- Updated: 2026-10-11T14:43:34.000Z
- Description: Qlik built Qlik Answers on Amazon Bedrock to give its 40,000+ customers grounded, sourced answers across structured and unstructured enterprise data. Learn how a layered, multi-agent architecture with cross-Region inference and Amazon Bedrock Guardrails delivers trusted AI at global scale.
- Author: Satish Das
- Tags: Cloud, Stirup Research

## Enterprise AI at Scale: Qlik’s Approach with Amazon Bedrock

Qlik Answers, a product built on Amazon Bedrock, addresses a critical challenge in enterprise environments: providing employees with fast, accurate, and verifiable answers to complex questions across diverse data sources. With over 40,000 customers globally, Qlik needed a solution that could scale across regions, support compliance requirements, and deliver consistent performance without compromising on data integrity or user experience.

The core challenge Qlik faced was not just building a powerful AI assistant, but ensuring that it could operate efficiently at scale while maintaining data sovereignty and regulatory compliance. This required a layered, multi-agent architecture that could handle a wide range of tasks—from simple lookups to complex, multi-source queries—without slowing down or becoming inconsistent.

Qlik’s solution involved a modular design that separates the system into distinct layers: an entry layer for user interaction, a routing layer for directing queries, an answer layer for generating responses, and a specialist agent layer for handling specific tasks. This architecture allows for the addition of new capabilities without disrupting the existing system, ensuring that the user experience remains consistent across all customer deployments.

One of the most critical components of this system is the grounding mechanism, which ensures that every answer is backed by verifiable sources. This is achieved through a combination of unstructured document indexing using Amazon OpenSearch Service and a grounding-validation check that compares generated answers against the source content. This process transforms grounding from a retrieval step into a production control, ensuring that all responses are accurate and reliable.

Amazon Bedrock plays a central role in this architecture by providing the necessary model flexibility, cross-Region inference capabilities, and security features. Qlik leverages Bedrock’s multi-model support to assign the most suitable model to each task, ensuring optimal performance without locking the system to a single model’s limitations. Additionally, Bedrock’s cross-Region inference (CRIS) allows Qlik to serve customers in 11 different regions while maintaining data residency where required, addressing compliance and data sovereignty concerns.

Qlik also uses Amazon Bedrock Guardrails to enforce content filtering, protect against prompt injection, and validate the grounding of generated answers. These security measures are applied at the model access layer, ensuring that all responses meet enterprise-grade standards before being delivered to users.

By building a system that separates routing from deep reasoning, standardizes on a single orchestration framework, and treats safety and grounding as system-level gates, Qlik has created a scalable, secure, and reliable AI solution that meets the needs of its global customer base. This approach not only improves user productivity but also ensures that AI adoption remains aligned with enterprise compliance and operational requirements.

**Source:** [AWS Machine Learning](https://aws.amazon.com/blogs/machine-learning/how-qlik-built-grounded-enterprise-scale-ai-with-amazon-bedrock/?ref=stirup.si). Analysis based on publicly available information; no hands-on testing is claimed.