How AI is transforming healthcare through clinical decision support, medical imaging, predictive diagnostics, and operational efficiency.
8
Use Cases
8
Companies
25
Tools Used
Companies
Popular Tools in Healthcare
AWSSign up to read complete case studies, access detailed metrics, and unlock all use cases.
Use Cases (8)
Humana replaced its legacy IVR system with an IBM Watson-based conversational voice agent that handles 7,000+ provider calls daily, completing inquiries in 2 minutes at one-third the previous cost.
Intermountain Health deployed Microsoft Dragon Copilot to 2,500+ clinicians, reducing time spent on notes by 27% per appointment and fighting clinician burnout with AI-generated clinical documentation.
Medlitix implemented UiPath medical record summarization with DeepRAG, cutting clinical review from 70 minutes to 6 minutes per case (90% faster) with 95% accuracy and $1.2M savings.
InpharmD's AI assistant, Sherlock, leverages Pinecone's vector database to deliver fast, accurate drug information to healthcare professionals. By embedding 30 million medical documents into a RAG pipeline, InpharmD achieved 70% better query accuracy, 95x faster first response times, and 80% cost savings on data storage.
UChicago Medicine, a leading academic health system, leveraged Salesforce Data Cloud, Marketing Cloud, and Agentforce to unify patient data and deliver hyper-personalized outreach at scale. In just four months, the team built 100 data-driven marketing segments, achieving a 60% campaign conversion rate and full ROI in under a year. The organization is now deploying Agentforce Voice to autonomously handle millions of nonclinical patient inquiries annually.
Epic Systems — the healthcare technology company behind MyChart, used by 195 million patients — deployed Claude Code across its entire workforce, not just engineers. Today, more than half of Claude Code usage at Epic comes from non-technical employees, including a pharmacist who built a fully interactive MyChart prototype without writing a single line of code.
AstraZeneca, one of the world’s largest pharmaceutical companies, unified 5,000 developers and scientists onto GitHub Enterprise, automated CI/CD with GitHub Actions, and deployed GitHub Copilot — achieving a 40% increase in developer velocity in its pilot program and generating 9 to 10 additional hours of productive output per developer each week. With drug development timelines measured in decades, the company views even marginal acceleration as directly impacting patient outcomes.
Giles AI, a London-based healthcare AI startup, built its medical research assistant on Google Cloud using Vertex AI, Gemini Pro, and Document AI to help researchers extract structured insights from millions of scientific articles. The platform achieved 95% accuracy in data extraction, a 98% agreement rate with human researchers, and helped one clinical customer cut research task time by 85%.