Overview
Murali Aravamudan is executive chairman of the board at Anumana, a digital health company using artificial intelligence to unlock the electrical language of the heart. Anumana was founded by nference and Mayo Clinic to accomplish this goal per the company about page. Aravamudan is described as a serial entrepreneur, inventor, and engineer who has built, led, and exited several successful media and telecom technology companies, and is co-founder of nference.
Anumana’s FDA-cleared ECG-AI LEF technology analyzes a standard 10-second ECG and detects patterns invisible to the human eye that reveal reduced heart function before traditional methods can catch it.
Role and company
As Executive Chairman, Aravamudan provides board leadership while Maulik Nanavaty serves as chief executive officer and Simos Kedikoglou, MD, as chief operating officer per Anumana’s leadership roster. Anumana’s name reflects Sanskrit anumana — inference — meaning to use observation, previous truths, and reason to reach a new conclusion.
The company combines massive clinical datasets, cardiovascular expertise from Mayo Clinic partnership, and AI to detect conditions including low ejection fraction using standard ECG workflows already performed thousands of times daily in clinical practice.
Background and career context
Anumana’s about page states Aravamudan co-founded nference and serves as executive chairman of Anumana’s board. He is characterized as a serial entrepreneur with exits in media and telecom technology before applying inference-based AI to cardiovascular medicine. The about page biography notes his 2005 entrepreneurial activities without detailing full career history on the cited excerpt reviewed.
Aravamudan’s nference connection links Anumana to a broader clinical AI data platform ecosystem — a structural advantage when training ECG algorithms on millions of ECG-echo pairs.
Company-building or leadership context
Anumana was founded by nference and Mayo Clinic, bringing together AI capabilities and cardiovascular clinical expertise. The company’s ECG-AI platform was modeled on nearly 2.9 million ECG-echo pairs and 676,000+ patients across diverse populations per Anumana data disclosures on its about page. FDA clearance means ECG-AI LEF has met standards for safety and effectiveness clinicians can trust in patient care.
Aravamudan’s chairman role reflects a governance model where nference’s founding entrepreneur guides strategy while CEO Nanavaty leads commercial and operational medical device execution.
Public milestones
Anumana reports latest clinical performance demonstrating 90.2% sensitivity and 85.1% specificity in detecting low ejection fraction per its about page. The company cites over 30 peer-reviewed publications, FDA clearance (K250652 for ECG-AI LEF), commercial deployment across healthcare systems, and established CPT codes and reimbursement pathways.
April 2026 FDA clearance for ECG-AI cardiac amyloidosis and March 2026 pulmonary hypertension algorithm clearances extend Anumana’s multi-condition ECG-AI portfolio beyond low ejection fraction detection.
Why their work matters
Anumana demonstrates that standard 12-lead ECGs — already ubiquitous in cardiology — can become early detection tools for heart failure and related conditions when AI reads electrical signals humans cannot reliably interpret. Aravamudan’s chairman leadership connects startup velocity with Mayo Clinic scientific rigor, a partnership model other ECG-AI vendors attempt to replicate.
For healthcare AI readers, Anumana sits at the intersection of diagnostic AI and existing billing workflows — distinct from de novo imaging AI requiring new hardware purchases.
Sources and references
Primary sourcing: Anumana About Us leadership section, reviewed July 10, 2026.
- Anumana — About Us (anumana.ai)
- Anumana — Homepage (anumana.ai)
Clinical performance statistics and FDA clearance references from Anumana about page disclosures only.