xCures

Learning Objectives

• Understand the medical-records problem xCures is built to solve
• Learn what the Clinical Clarity Engine produces and who uses it
• See where structuring clinical data helps and what still needs human judgment

What Is xCures?

xCures is a health-AI company that turns messy, scattered medical records into clean, structured data a clinician can actually use. A single patient's history is usually spread across many labs, hospitals, imaging centers, and electronic health record systems, and it arrives as a pile of mismatched documents — PDFs, scans, faxes, and free-text notes. That fragmentation slows down care and makes it hard to see the full picture at the moment a decision is being made. xCures uses AI to pull all of that together and normalize it into evidence-grade, structured data.

The company was spun out of the cancer non-profit Cancer Commons in 2018 by co-founder and chairman Marty Tenenbaum. It started in oncology — assembling complete treatment histories for patients with advanced cancer so they could find options — and has since expanded across clinical domains. Its platform, the Clinical Clarity Engine, is used by life-sciences companies, researchers, and care teams; named customers include Exact Sciences, Caris Life Sciences, and Novocure. In June 2026, xCures raised a $46 million round led by Innovius Capital.

Core Capabilities

Record Aggregation

xCures gathers a patient's records from across the many sites where care happened — labs, hospitals, imaging centers, and electronic health record systems — into one place.

AI Extraction and Structuring

The Clinical Clarity Engine uses AI to read unstructured documents and extract the key facts — diagnoses, treatments, lab results, and timelines — normalizing them into structured, decision-ready data.

Decision-Ready Patient Histories

It builds a clear, evidence-backed timeline of a patient's care, the kind of summary that helps clinicians and researchers act without digging through hundreds of pages.

Research and Trial Support

Because the data is structured, it can power research, real-world-evidence studies, and clinical-trial matching — connecting patients to options that fit their specific history.

Strengths

• Solves a real, expensive bottleneck — unstructured records are a universal drag on care and research
• Deep clinical roots — built on years of work in oncology, the most complex corner of medicine
• Scale — more than 300 million records processed from over 550,000 sites
• Credible customers — used by Exact Sciences, Caris Life Sciences, and Novocure

Limitations & Considerations

• Not a diagnostic tool — it organizes and structures information; clinicians make the medical decisions
• Accuracy matters enormously — extraction errors in a medical record carry real risk, so human review of the output is essential
• Privacy and compliance — handling patient data means strict regulatory and security obligations
• Enterprise-focused — aimed at health systems, researchers, and life-sciences teams, not individual patients self-serving

Best Use Cases

Getting Started

1. Visit xcures.com — the platform is sold to institutions, not self-serve
2. Identify the use case: assembling patient histories, powering research, or supporting trial matching
3. Work with xCures to connect record sources and define the structured output you need
4. Treat the structured data as decision support — clinicians and researchers verify and act on it

Key Takeaways

• xCures turns scattered, unstructured medical records into structured, decision-ready clinical data
• Its Clinical Clarity Engine grew out of oncology work at Cancer Commons and now spans clinical domains
• It has processed more than 300 million records from over 550,000 sites, with customers including Exact Sciences, Caris, and Novocure; it raised $46 million in June 2026
• It organizes information so people can decide faster — it does not replace clinical judgment, and accuracy and privacy are paramount