What challenges did Kry face before AI implementation?

Healthcare systems face increased demand from aging populations and chronic diseases. Many rural areas lack sufficient access to doctors or healthcare resources. High administrative burden on clinicians reduces time for patient care. Drug discovery is costly and time-consuming. Medical imaging and pathology are intensive and often delayed, impacting timely diagnosis.

What was the impact of the AI solution?

Health First saw a 90% improvement in data processing with Azure Synapse Analytics. Epic’s EHR automation reduced clinician workload and improved operational reporting efficiency.

Source

MicrosoftExpandedProductionEvidence: Medium60/100

Scandinavian Healthcare Providers Enhance Patient Outcomes with AI-Powered Solutions

Use case typeAI development platformUpdated Jun 13, 2026

Scandinavian healthcare institutions, notably in Sweden and Norway, are leveraging advanced Microsoft Azure and OpenAI technologies to transform their clinical and operational workflows. Key use cases include the integration of Azure OpenAI Service into Epic's electronic health record (EHR) platform, enabling automated message drafting and operational reporting, and Kry’s telehealth solution, which provides AI-powered triage and multilingual care for millions of patients. Additional innovations span accelerated medical imaging via Project InnerEye, radiotherapy planning tools at Cambridge University Hospitals, global digital pathology with PathPresenter, and scalable data architecture with Azure Synapse Analytics. These implementations improve diagnostics, enhance access in underserved areas, lower administrative burdens, and support responsible AI governance, fostering efficiency and equitable patient care across diverse populations.

Organization: Kry
Industry: Healthcare
Location: Sweden
Published: June 2023

Reported outcomes

Impact: +90%

Other quantified impact

Planned next steps

The source says the organization plans to achieve Time: 2.5× lower.

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

Normalized claim

Time: 2.5 x decrease

azure.microsoft.comJun 28, 2023Blog postInferred claimMedium evidence strength

Radiotherapy planning time reduced 2.5x at Cambridge, improving treatment outcomes.

Last evidence check: Jun 1, 2026

Normalized claim

Quantified impact: 90% increase

azure.microsoft.comJun 28, 2023Blog postInferred claimMedium evidence strength

Health First saw a 90% improvement in data processing with Azure Synapse Analytics.

Last evidence check: Jun 1, 2026

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

Customer: Kry, Addenbrooke's Hospital (Cambridge University Hospitals NHS Foundation Trust)
Provider: Microsoft
Maturity: Production
Linked source: azure.microsoft.com

Scandinavian healthcare institutions, notably in Sweden and Norway, are leveraging advanced Microsoft Azure and OpenAI technologies to transform their clinical and operational workflows

Customer identity supportedSource describes one deploymentMaturity supported

Primary read

Use case focus

Showing 3 of 5

1virtual triage
2AI-powered EHR automation
3medical imaging analysis

Kry implemented AI-driven telehealth for triage, multilingual interaction, and broad access.
Epic integrated Azure OpenAI to automate clinical communications and reporting.
Project InnerEye employed Azure-based AI to speed imaging analysis and radiotherapy planning.
Digital pathology and operational analytics adopt Azure cloud and Power BI for big data scalability and accessibility.
Responsible AI frameworks and integrated safety protocols ensure ethical deployment.

Technologies

Azure AI Azure OpenAI Azure Health Bot Azure Synapse Analytics Power BI

Health First saw a 90% improvement in data processing with Azure Synapse Analytics.
Epic’s EHR automation reduced clinician workload and improved operational reporting efficiency.

Architecture

Patient data is managed and analyzed using Azure-based architectures: EHR workflows in Epic leverage Azure OpenAI Service for automated messaging and operational insights. Kry's telehealth uses cloud-based AI-powered triage and language translation across multiple platforms. Project InnerEye and digital pathology integrate machine learning pipelines in Azure for image analysis, while analytics and reporting rely on Azure Synapse Analytics and Power BI.

Sources & evidence1

Evidence: Medium60/100Evidence strength