Partner Case Study | Aiforia

For years, the promise of AI has been to empower people to work more efficiently, make better decisions, and focus attention where it matters most. In healthcare, that promise carries particular weight. As diagnostic workloads rise and specialist shortages continue to strain healthcare systems worldwide, organizations are increasingly exploring how AI can support clinicians without replacing the expertise at the center of patient care.

Founded in 2013 in Helsinki, Finland, Aiforia is a digital pathology software company focused on bringing AI into clinical diagnostics and medical research. A long-standing Microsoft partner, Aiforia uses Microsoft Azure to help pathology teams analyze digitized tissue samples more efficiently and consistently, transforming historically manual workflows into scalable, AI-assisted processes. With 5,000 users across 50 countries, Aiforia has analyzed more than 1 million images and developed thousands of AI models.

Aiforia’s work spans clinical diagnostics and research applications, including CE-IVD-certified diagnostic support tools and custom AI model development for pathology labs. The CE-IVD designation signifies that a solution meets European In Vitro Diagnostic Regulation (IVDR) requirements for clinical diagnostic use, placing security, governance, and reliability at the center of how these systems are developed and deployed. Using Microsoft technology, Aiforia is helping healthcare organizations securely manage and analyze massive pathology image datasets—and supporting increasingly advanced AI models within highly regulated clinical environments.

That opportunity is now taking shape within the United Kingdom’s National Health Service (NHS), where Aiforia is working with University Hospital Southampton NHS Foundation Trust to explore how AI-assisted pathology could help clinicians manage growing diagnostic demands, specifically related to lung cancer, with greater speed, accuracy, and consistency.

Modernizing pathology workflows for growing healthcare demands

Southampton serves a large and complex patient population within the NHS, where pathology teams face growing pressure to deliver accurate diagnoses quickly and consistently. Like many healthcare organizations worldwide, Southampton is navigating rising diagnostic workloads alongside a shortage of trained specialists, creating an urgent need for tools that can support clinicians without disrupting the expertise and oversight at the center of patient care.

That challenge is particularly acute in pathology, where specialists analyze high-resolution digitized tissue samples that guide critical treatment decisions, including cancer care. Despite advances in healthcare technology, many pathology workflows still rely heavily on manual interpretation. Pathologists are manually reviewing and interpreting massive and highly complex histology landscapes while attempting to maintain precision, consistency, and governance across increasingly demanding caseloads.

Maintaining that pace and consistency can be difficult even among experienced clinicians. Small differences in interpretation can create inter-observer and intra-observer variability, particularly in complex diagnostic areas like quantification of PD-L1 biomarkers in lung cancer diagnostics. For healthcare organizations already under operational strain, improving standardization while reducing manual workload has become a priority.

Within the NHS, healthcare leaders have been exploring how digital pathology and AI-assisted analysis could help address those pressures without removing clinicians from the decision-making process. Through the PathLAKE Plus procurement framework, Aiforia was selected as an approved AI vendor supporting more than 25 NHS trusts. University Hospital Southampton NHS Foundation Trust became the first NHS trust in the UK to deploy Aiforia’s technology, establishing an early implementation process for broader NHS adoption.

Continue reading here

Explore all case studies or submit your own

Subscribe to case studies tag to follow all new case study posts. 

Don't forget to follow this blog to receive email notifications of new stories!