Few fields stand to gain more from artificial intelligence than medicine. From compressing drug-discovery timelines to reading scans with superhuman consistency, the companies below are rewriting what is possible in healthcare.
AI is revolutionizing healthcare, from accelerating drug discovery to enabling more accurate diagnostics and personalized treatment.
Tempus AI
Chicago, United States
Tempus provides a platform combining comprehensive clinical and molecular data with artificial intelligence, primarily serving the oncology space. Their core offering is an operating system built upon the world’s largest library of such data, enhanced by recent advancements in generative AI like their clinical co-pilot, David, and digital pathology capabilities acquired through Paige. Tempus targets physicians, pharmaceutical companies, and patients seeking data-driven insights to improve cancer treatment decisions and accelerate drug development.
Babylon Health
London, United Kingdom
Babylon Health develops a platform offering AI-powered triage, remote consultations, and diagnostic tools, most notably through its Babylon 360 and GP at Hand services. Their core AI capabilities center on a deep learning system trained on millions of medical records to provide preliminary symptom assessment and risk prediction, alongside automated appointment scheduling and clinical note summarization. Initially focused on the UK’s National Health Service and direct-to-consumer offerings, Babylon has expanded internationally and achieved notable partnerships to deploy its technology in Rwanda and Canada, aiming to increase access to primary care.
Freenome
South San Francisco, United States
Freenome develops a blood-based, multiomics screening platform designed for early cancer detection, utilizing both genomic and proteomic biomarkers. Their core technology employs machine learning algorithms to analyze complex patterns in blood samples, aiming to detect cancer signals prior to symptom onset and improve screening accessibility. Currently focused on colorectal cancer with their CRC-DETECT test, Freenome is conducting clinical trials to validate performance and expand their platform to detect multiple cancer types, with a goal of increasing survival rates through earlier diagnosis.
Insitro
South San Francisco, United States
Insitro leverages high-throughput phenotypic screening and machine learning to build predictive models of human biology, focusing initially on diseases like NASH and heart failure. Their platform combines large-scale experimental data – including cellular assays and human genetic data – with proprietary machine learning algorithms to identify and validate drug targets and predict clinical trial success. Notably, Insitro has established collaborations with pharmaceutical companies like Bristol Myers Squibb and Roche to apply their technology to specific disease areas and advance novel therapeutics.
Collective Health
San Francisco, United States
Collective Health is a technology-enabled third-party administrator (TPA) that integrates and optimizes employee health benefits administration for self-funded employers. Their platform utilizes data analytics and AI-driven personalization to connect medical, pharmacy, and ancillary benefits into a single, user-friendly experience. This solution aims to reduce administrative costs and improve member engagement by providing a simplified and connected benefits journey for employers and their employees.
Zipline
South San Francisco, United States
Zipline Rwanda operates an autonomous drone delivery service focused on rapidly distributing critical medical supplies, including blood and vaccines, to remote and underserved healthcare facilities. Their core technology is a fully integrated platform encompassing drone aircraft, automated logistics software, and a proprietary demand forecasting system to optimize inventory and delivery routes. Targeting the healthcare sector and governments in regions with challenging infrastructure, Zipline provides instant, reliable access to essential medical products, reducing delivery times and improving health outcomes.
Butterfly Network
Burlington, United States
Butterfly Network develops handheld, whole-body ultrasound devices integrated with AI-powered software for point-of-care imaging. Their flagship product, the Butterfly iQ3, utilizes a single probe to deliver diagnostic imaging across a wide range of clinical applications. Butterfly Network serves diverse markets including individual medical practices, large healthcare systems, and medical education programs, offering a portable and accessible alternative to traditional ultrasound technology.
Alan
Paris, France
Alan is a French digital health insurance provider leveraging AI-powered automation to streamline claims processing and enhance preventative healthcare services. Their core offering is a full-stack health insurance platform designed for SMEs and individuals, integrating insurance, preventative care, and telemedicine features. Alan differentiates itself by focusing on a proactive, data-driven approach to employee wellbeing and simplified administrative processes for businesses.
Omada Health
San Francisco, United States
Omada Health delivers virtual chronic disease management programs focused on behavior change interventions for conditions like diabetes, hypertension, and mental health. Their core offering utilizes AI-powered personalization to adapt program content and coaching based on individual member data and progress, delivered through a mobile app and connected devices. Omada targets health plans and employers seeking cost-effective, accessible chronic care solutions, often offered at no cost to members through benefit programs.
HeartFlow
Redwood City, United States
HeartFlow is a US-based medical technology company that leverages AI to improve the diagnosis and management of coronary artery disease (CAD). Their primary product utilizes AI analysis of standard Coronary Computed Tomography Angiography (CCTA) scans to create a personalized 3D model of the patient’s coronary arteries, assessing both anatomy and blood flow. This technology is targeted towards cardiologists and healthcare systems seeking to reduce false positives/negatives in CAD diagnosis and enable more informed, patient-specific treatment decisions.
Frequently asked questions
How is AI used in healthcare today?
AI accelerates drug discovery, improves diagnostic accuracy in medical imaging, personalizes treatment plans, and automates clinical and administrative workflows.
Can AI speed up drug discovery?
Yes. AI models can predict molecular properties and protein structures, helping researchers narrow billions of candidate compounds to a promising few far faster than traditional methods.
Is AI in medicine regulated?
Healthcare AI tools that influence diagnosis or treatment typically require regulatory clearance and rigorous validation before clinical use, given the patient-safety stakes.
Will AI replace doctors?
The prevailing view is augmentation, not replacement: AI handles pattern recognition and routine analysis so clinicians can focus on judgment, communication, and care.