AI infrastructure for cardiac care

Turn cardiac data into clinical actions.

Help your team review more data, prioritize what matters, and scale clinical operations.

Request a demo → See how it works
Higher review capacity
Faster, more consistent triage
Seamless integration into your workflow
Clinician reviewing a patient monitoring dashboard on XAI.health
Built for real-world cardiac monitoring

Trusted by the teams who keep hearts healthy.

XAI.health provides AI-powered tools that fit into your clinical workflow — so you can deliver high-quality care at scale, with confidence.

For Clinics

Reduce review burden, surface critical findings, and focus your physicians on what matters most.

Physician reviewing cardiac dashboard at a bright clinic desk

For IDTFs

Scale monitoring operations, improve consistency, and support higher patient volumes.

Cardiac monitoring station showing rhythm analysis and vitals
Proven in the clinic

Built by the team that took AI-ECG from research to the bedside.

Not projected outcomes — published, peer-reviewed, and regulatory results from the AI-ECG program our founders led at Mayo Clinic.

2019
First AI-ECG for low ejection fraction published
Nature Medicine
22,000+
Patients in the randomized EAGLE AI-ECG trial
Nature Medicine, 2021
32%
Increase in new low-EF diagnoses vs. usual care
EAGLE trial
FDA
Cleared AI-ECG algorithms, with CMS reimbursement established
From device report to reviewed summary

Device PDF in. A reviewed summary out.

Today, XAI.health ingests the PDF reports generated by ILR, pacemaker, ICD, and CRT devices — from Boston Scientific, Abbott, Medtronic, and Biotronik — applies AI to prioritize findings, and uses an LLM to draft a patient summary your clinician reviews and finalizes.

1
Ingest — device PDF reports are extracted and normalized on the way in.
2
Interpret — AI reviews the data and prioritizes what's clinically relevant.
3
Draft & review — an LLM drafts a patient summary; your clinician reviews and finalizes it.
Device PDF
→
AI interpretation
→
LLM-drafted summary
Leadership

Founded by the team that pioneered AI-ECG.

Our founders led the Mayo Clinic program that took AI-ECG from a research idea to a randomized trial, FDA clearance, and daily use in routine clinical practice.

Zachi Attia

Zachi Attia, Ph.D., MBA

Co-Founder & CEO
Director of AI in Cardiology, Mayo Clinic · Associate Professor of Medicine, Mayo Clinic College of Medicine and Science

First author of the 2019 Nature Medicine paper that opened the field of AI-ECG, and of multiple Nature Medicine and Lancet AI-ECG papers since. Leads a team of Ph.D. AI engineers across Mayo Clinic's cardiology, preventive cardiology, and AI & informatics departments.

300+ publications Ph.D., Univ. of Minnesota MBA, MIT
Paul A. Friedman

Paul A. Friedman, M.D.

Co-Founder & CMO
Chair, Department of Cardiovascular Medicine, Mayo Clinic, Rochester

Board certified in cardiovascular medicine and clinical cardiac electrophysiology. Holds ~60 issued patents spanning devices, signal processing, and applied AI — a 2022 Mayo Clinic Distinguished Inventor and Fellow of the National Academy of Inventors.

400+ publications ~60 patents M.D., Stanford

Let's build a more efficient future for cardiac care.

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Works with your data