Top 10: AI Platforms in Healthcare

AI platforms are emerging as essential tools in healthcare as providers pursue quicker insights from intricate clinical data.

By integrating intelligence into daily workflows, they support clinicians in making improved decisions, alleviating strain on overburdened systems and dedicating greater time to patient care.

As expenses grow and demands intensify, AI platforms are forming a more robust healthcare model that could be more predictive and personalised.

Healthcare Digital explores the Top 10 AI platforms being used in the healthcare sector. 

10. Butterfly Network

Headquarters: Massachusetts, US
CEO: Joseph DeVivo
Year founded: 2011
Number of Employees: ~200

Butterfly Network utilises AI within portable ultrasound technology, merging semiconductor-driven hardware with cloud-based software and assisted imaging capabilities.

The platform's AI functions enable image enhancement, automatic measurements and clinical decision-making assistance at the point of care.

Although the system is more hardware-focused than other platforms featured, it serves an increasingly important function in broadening diagnostic imaging access across primary care, emergency and remote healthcare environments.

9. Caption AI (Caption Health, part of GE HealthCare)

Headquarters: California, US
CEO: Peter J. Arduini (GE Healthcare)
Year founded: 2013

Caption AI provides AI-powered ultrasound technology allowing healthcare professionals with minimal imaging training to obtain diagnostic images of superior quality.

The platform integrates within GE HealthCare's broader ecosystem and utilises automated workflows alongside real-time guidance to enhance accessibility.

While its specialised focus restricts overall scope, enterprise-level implementation via GE HealthCare provides substantial clinical coverage

8. PathAI

Headquarters: Massachusetts, US
CEO: Andy Beck
Year founded: 2016
Number of Employees: ~300

PathAI is a dedicated AI platform specialising in digital pathology, using machine learning to enhance diagnostic precision and streamline workflow processes.

The technology assists pathologists and life sciences companies in image analysis, disease identification and biomarker identification.

Though more limited than enterprise platforms, PathAI fulfils an essential function in oncology diagnostics and pharmaceutical development.

7. Merative

Headquarters: Michigan, US
CEO: Gerry McCarthy
Year founded: 2022
Number of Employees: ~3,000

Merative offers data, analytics and AI solutions for healthcare payers, providers and life sciences companies.

Created from IBM Watson Health assets, its platforms enable outcomes research, clinical decision-making and population health management.

Not as clinician-focused as emerging AI players, Merative is a major enterprise analytics partner for healthcare systems.

6. Truveta

Headquarters: Washington, US
CEO: Terry Myerson
Year founded: 2020
Number of Employees: ~400

Truveta operates a real-world data platform constructed from de-identified clinical information sourced from health systems.

Through AI and analytics, the platform enables research, population health insights and therapy development.

Strength lies in longitudinal data depth and system-level collaboration beyond front-line clinical tools.

5. Tempus

Headquarters: Illinois, US
CEO: Eric Lefkofsky
Year founded: 2015
Number of Employees: 2,300+

Tempus is a precision medicine platform using AI to analyse clinical and molecular data, with oncology as its primary focus.

The technology enables personalised treatment decisions, clinical trial matching and research insights.

By integrating genomics, imaging and real-world data, Tempus positions as a data-driven medicine leader.

4. Aidoc

Headquarters: Tel Aviv, Israel
CEO: Elad Walach
Year founded: 2016
Number of Employees: 500+

Aidoc provides an enterprise AI platform for medical imaging, allowing health systems to implement, oversee and expand multiple AI algorithms throughout clinical workflows.

The orchestration layer enables prioritisation, triage and clinical collaboration beyond radiology.

The company differentiates itself through established governance, integration capabilities and clinical adoption.

3. Google Cloud Healthcare

Headquarters: California, US
CEO: Thomas Kurian
Year founded: 2008
Number of Employees: 50,000+

Google Cloud Healthcare provides an AI-native platform centred on its Healthcare API and Data Engine.

The platform facilitates interoperability, population health analytics and advanced machine learning across clinical and research data.

Supported by Google's AI capabilities, it demonstrates strength in large-scale analytics and life sciences applications.

2. AWS HealthLake

Headquarters: Washington, USA
CEO: Matt Garman
Year founded: 2006
Number of Employees: 125,000+

AWS HealthLake is a fully managed platform built to store, transform and analyse clinical information through AI and machine learning.

Built on Fast Healthcare Interoperability Resources (FHIR) standards, it supports healthcare AI applications globally.

HealthLake centres on interoperability and integration with the AWS ecosystem, positioning it as a foundational tool for digital health innovation.

1. Microsoft Dragon Copilot

Headquarters: Washington, US
CEO: Satya Nadella
Year founded: 1975
Number of Employees: 220,000+

Microsoft Dragon Copilot stands as the leading AI platform designed for clinicians in healthcare.

By integrating ambient clinical intelligence, gen AI and automated workflows, it decreases administrative workload whilst enhancing documentation standards and patient care.

Integrated into Microsoft's wider healthcare and cloud infrastructure, the platform is establishing itself as essential to daily clinical operations.