AI in Qlik Cloud
Overview
Qlik Cloud makes use of AI throughout our services. This includes, all types of AI including Agentic AI, Generative AI & machine learning. When Adding new AI based services, or enhancing existing services with AI, Qlik's priority is to put the protection of customer data first.
Design principles for AI on Qlik Cloud
Qlik believes the productivity and efficiency gains AI provide should not require customers to take risks with their data. As a company, Qlik's approach to AI is based on these key principles:
- Reliability
- Customer Control
- Transperency
- Explainability
- Inclusive
These principles are explained at our Trust & AI page. Based on these general principles, our design principles ensure the solutions we deliver meet these requirements giving our customers confident that leveraging AI with Qlik does not compromise their data security & governance needs.
The based on Qlik's overarching principles, AI principles and governance requirements, the following design principles apply to our AI initiatives at Qlik:
- Qlik does not, nor do we allow our providers to train their AI systems on customer data.
- Qlik Cloud is a highly governed and audited platform, holding many certifications and accreditations ( see Trust ). Qlik complies with the relevant laws applicable including the EU AI act for Limited risk and General risk use-cases. Any design decisions must align with the requirements of these laws, certifications and accreditations.
- AI compliance reviews are conducted as part of our product development processes to ensure our AI implementations align with our general AI principles.
- Qlik does not pass customer data to 3rd party AI services. Data is pre-filtered and pre-processed into vectors (a mathematical representation of data as a list of numbers) before being passed to the AI. Only the minimal vectors required for the question are passed.
We also apply our general cloud design principles to AI, namely:
- Qlik Cloud is a no view service. This means neither Qlik employees, our cloud providers, nor any parties other than the customer themselves can see the customers data. Our AI initiatives must meet this requirement also.
- Qlik cloud uses multiple layers of encryption (optionally using customer provided encryption keys) for all data stored on the platform including AI & unstructured data.
- All data moving into and out of Qlik Cloud (including AI) is secured with TLS.
Guardrails
When interacting with large language models (LLMs) Qlik applies a number fo guardrails to minimize risks for our customers:
- LLM monitoring for harmful content. Qlik scans and rejects questions that contain invisible text or prompt injections.
- Sanitization of Personal Identifying Information (PII) and secrets.Qlik detects and removes PII data and secrets when sending data to the LLM. The detected information is added back when providing responses.
- Hallucinations. Qlik mitigates hallucinations by detecting contextual relevance in the provided content. Additionally. users can view the content used as a source to verify responses.
Data Sovereignty
When a Customer creates their Qlik Cloud tenant, they are able to choose the region their tenant resides in. A customer's data does not leave their chosen region by default. Due to the speed of rollout of some AI services, as well as resource constraints from our our providers, certain features may necessitate limited data to be sent securely to another region. Where this is required, customers must opt-in to this. Qlik will not transfer data to other regions without the customers express authorization.
Cross-region data processing
Certain AI features in Qlik cloud require customers to allow Cross-region data processing. Enabling cross-region data processing allows Qlik Cloud to temporarily send the data required for processing to the AWS region where the service is available, process the request there, and return the results. Enabling cross-region data processing does not give Qlik or AWS access to your data. This requirement exists due to the high demand for AI services and limited availability of hardware from AWS.
So what does this mean for my data:
- All data at rest including logging is stored encrypted in the Customer's tenant in the customers choses region using the customers own encryption keys.
- Data sent between AWS regions is encrypted with Qlik's Encryption keys and travels through the secure AWS private network with end-to-end encryption for data in transit.
- No data is persisted in the other regions.
For a detailed underatanding of these processes at AWS, see Securing Amazon Bedrock cross-Region inference
Authorization & AI in Qlik Cloud
AI services in Qlik cloud fully respect any configured authorzation in Qlik Cloud. Access to applications, files and connections rely on permissions granted to the spaces those assets reside in. Within Applications, our AU services are bound by any section access configured for that application. If a user is restricted from data when using the application in a conventional way, they will also be restricted when interacting though AI.
AI Services in Qlik Cloud
AI is used throughout Qlik Cloud in many areas. Broadly speaking, our AI services fit into two key areas:
- Specific AI services and capabilities in Qlik Cloud
- AI Accelerators and helpers for non-AI services and capabilities in Qlik Cloud
AI services and capabilities in Qlik Cloud
The following AI services in Qlik Cloud do not require Cross-region data processing to function:
- Qlik answers (legacy assistants only)
- Qlik Predict
The following AI services are available in Qlik Cloud that rely on Cross-region data processing to function:
- Qlik answers (excluding legacy assistants)
- MCP Server
- Discovery Agent
AI Accelerators and helpers
The following components of Qlik Cloud Analytics & Qlik Talend Cloud are able to make use of AI if enabled (see the second level features), but can operate without AI if so desired.
Pipelines
- AI SQL assistant. For more information, see Generating a SQL transformation from a text prompt .
- AI model recommendations. For more information, see Creating a data model .
API Designer
- Generate contract. For more information, see Creating an API with AI Assistant (Talend help).
Data governance
- AI data quality validation rule generation. For more information, see Working with validation rules .
- AI-generated descriptions. For more information, see Generating an AI-based description.