What challenges did UNIQA Insurance Group face before AI implementation?

Claims handlers had to manually read and reconcile unstructured medical referral letters and invoices in multiple formats, which slowed claims processing, increased costs, and hurt customer satisfaction. The legacy claims system was not designed for modern data exchange and had to be integrated with Azure services via APIs.

Source

MicrosoftEvidence: Medium50/100

UNIQA SEE accelerates health insurance claims processing with Azure AI + Azure Document Intelligence + Azure OpenAI

Use case typeClaims automationUpdated Jun 13, 2026

UNIQA SEE faced fragmented and complex medical referral letters and invoices, heavy manual document review and validation, call center reliance, and long claims processing cycles.

Organization: UNIQA Insurance Group
Industry: Insurance
Location: Austria
Published: June 2026

Reported outcomes

80-93.3%

timeTime & speed

Strategic outcomes

New product / capabilityBuilt AI-driven medical referral processingNew product / capabilityLaunched digital self-service submission appSpeed & agilityAccelerated claims processing workflowCustomer experience & trustImproved customer satisfaction with faster responses

Catalog median for time & speed deployments: −50% across 312 reported metrics. Compare benchmarks →

Why do we believe this?Outcome claims, sources, and evidence checks

Normalized claim

Time: 80-93.3% decrease

Microsoft Customer StoryJun 7, 2026Customer storyInferred claimMedium evidence strength

Health claims processing time dropped from 15-30 minutes to 2-3 minutes, call center volumes decreased, employees were freed for higher-value work, and customer satisfaction improved with faster claim responses.

Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks

Customer: UNIQA Insurance Group, UNIQA SEE
Provider: Microsoft
Maturity: Unknown
Linked source: Microsoft Customer Story

No explicit deployment-stage evidence found.

Customer identity supportedSource describes one deploymentMaturity evidence evaluated

Primary read

Use case focus

Showing 3 of 4

1Claims Processing
2Document Processing
3Workflow Automation

Claims handlers had to manually read and reconcile unstructured medical referral letters and invoices in multiple formats, which slowed claims processing, increased costs, and hurt customer satisfaction.
The legacy claims system was not designed for modern data exchange and had to be integrated with Azure services via APIs.

UNIQA SEE built an end-to-end, AI-driven medical referral solution using Microsoft Azure AI, Microsoft Foundry, Azure Document Intelligence, and Azure OpenAI.
The solution standardized document structure with Azure Document Intelligence templates and readings, extracted and semantically matched referral and invoice data with Azure OpenAI, and integrated the results into the core claims system via APIs.
UNIQA SEE also launched a digital self-service web and mobile app for customers to submit referral letters.

Technologies

Azure AI Microsoft Foundry Azure AI Document Intelligence Azure OpenAI

Architecture

Claims documents from multiple providers are standardized with Azure Document Intelligence. Azure OpenAI is used to extract, interpret, and semantically match referral and invoice data. The output is integrated into the core claims system via APIs, supported by Microsoft Foundry collaboration and a customer self-service web and mobile app for document submission.

Sources & evidence1

Evidence: Medium50/100Evidence strength