MedAI Verdict
Decision support

Clinical Decision Support

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Anumana

by Anumana  ·  US

Last verified

ECG-AI software that flags low ejection fraction, pulmonary hypertension and cardiac amyloidosis from standard 12-lead ECGs.

At a glance

Pricing
No public price. The pricing page returns 404; the site offers a demo request only.
HIPAA
Not disclosed
SOC 2
Not disclosed
EHRs
—
Founded
—
HQ
US
On this page

Independent score  ·  By our public rubric

37/100Competitive

Editorial rating 2.5 / 5

How it’s computed →
  • Regulatory & Compliance
    12/22

    FDA cleared (4 K-numbers on record)

  • Clinical Integration
    0/11.6

    No EHR integrations listed

  • Evidence Strength
    14.7/30

    3 peer-reviewed papers

  • Vendor & Market
    3/18

    Seed-stage or unfunded

  • Sentiment & Transparency
    1.3/2.5

    Pricing on request, no public amounts

▸ Show all 11 dimensions

Regulatory & Compliance

  • FDA clearance12/12

    FDA cleared (4 K-numbers on record)

  • HIPAA / SOC2 / BAA0/10

    No public HIPAA/SOC2/BAA attestation

Clinical Integration

  • EHR integrations (count)0/6

    No EHR integrations listed

  • Top-3 EHR coverage (Epic / Oracle / Athena)0/5

    None of the top-3 EHRs covered

  • Bidirectional write-back0/1

    No bidirectional write-back documented

Evidence Strength

  • Peer-reviewed papers15/21

    3 peer-reviewed papers

  • RCT / meta-analysis / systematic review0/9

    No RCT, meta-analysis, or systematic review

Vendor & Market

  • Funding & adoption signal3/12

    Seed-stage or unfunded

  • Years in market0/6

    Founded year not recorded

Sentiment & Transparency

  • Pricing transparency1/3

    Pricing on request, no public amounts

Scored November 2, 2026 · Public scoring method v1.2.0

ECG-AI software that flags low ejection fraction, pulmonary hypertension and cardiac amyloidosis from standard 12-lead ECGs.

No public price. The pricing page returns 404; the site offers a demo request only.

Evidence record

FDA decisions
Peer-reviewed

3 studies on PubMed: 3 other, published 2023 to 2026. Read the literature summary

Verification
  • Score computed November 2, 2026, method 1.2.0
  • Review written November 2, 2026
Cite this record

MedAI Verdict, Anumana record, https://medaiverdict.com/tools/anumana, version November 2, 2026

Bottom line

Anumana, a Mayo Clinic and nference joint venture based in Cambridge, Massachusetts, sells ECG-AI algorithms that read a standard 12-lead ECG and send a clinical decision support notification into the EHR. It holds four 510(k) clearances for low ejection fraction, pulmonary hypertension and cardiac amyloidosis. It suits a health system that wants those flags raised from 12-lead ECGs it already acquires. Access is by demo request, so a practice that wants a posted price or a device to buy off the page is not served.

Which FDA decisions are Anumana's?

All four are 510(k) clearances:

  • K232699 (September 28, 2023), Low Ejection Fraction AI-ECG Algorithm, product code QYE. Its predicate is Viz HCM, authorized through De Novo DEN230003 for Viz.ai, which is another company's authorization.
  • K250652 (July 28, 2025), ECG-AI Low Ejection Fraction 12-Lead algorithm.
  • K252360 (March 28, 2026), ECG-AI Pulmonary Hypertension 12-Lead algorithm, product code SAT.
  • K253801 (April 7, 2026), ECG-AI Cardiac Amyloidosis 12-Lead algorithm, product code SHP. The vendor's site dates it April 8.

Where do the algorithms appear in the literature?

Thirteen PubMed hits match the company by name or affiliation. Nine concern its work, many with Mayo and nference authors, which makes them vendor-linked. Titles name these, and whether each one tests the cleared algorithm is not verified:

  • PMID 41377035 (Am Heart J Plus, 2026), a pragmatic trial of the Anumana clinical decision support tool for guideline-directed management, with PMID 42828092 as a comment on it.
  • PMID 40276542 (Am Heart J Plus, 2025), a multicenter pragmatic implementation of AI-ECG software to identify low LVEF.
  • PMID 41547169 (JACC Advances, 2026), multisite external validation of an AI-ECG algorithm for low EF.
  • PMID 38936966 (European Respiratory Journal, 2024), ECG-based AI for early pulmonary hypertension detection.

The vendor says the low EF model was built on about 2.9 million ECG and echo pairs from more than 676,000 patients and reports 90.2% sensitivity and 85.1% specificity, attributed to its own data. It claims more than 30 peer-reviewed publications.

How does it fit into a hospital?

The vendor says the software accepts XML or DICOM waveform files, that no PHI is exported for external processing, and that the algorithms deploy within EHRs. No EHR or ECG management system is named. The homepage lists CPT III codes for charge capture and calls the product "eligible for reimbursement today". It describes low EF as available for clinical use in the US and EU and cites no CE certificate. Beyond a vulnerability disclosure page, the homepage and About page cite no security certification, and they list no price or customer.

Ownership and funding

The company launched in 2021 as a joint venture of Mayo Clinic and nference. Maulik Nanavaty is CEO and Murali Aravamudan executive chairman. MedCity News coverage reports a $25.7 million Series A at launch and a $60 million Series B by July 2022. CB Insights shows a Series C and $153.1 million in total, which is unverified.

The verdict

The homepage cites CPT III codes for charge capture and calls the product eligible for reimbursement. A buyer who wants single-lead or wearable ECG screening is in a different category.

Editorial review last generated November 2, 2026. Synthesized from clinician sentiment, peer-reviewed coverage, and our editorial silo picks. Refined by hand where vendor facts change.

What it costs

All tiers are custom-quoted. The vendor does not publish per-provider list pricing.

TierMonthlyAnnualNotes
EnterpriseNot statedNot statedNo public price. The pricing page returns 404; the site offers a demo request only.

Source: vendor pricing page. Last checked November 2, 2026.

What deploys cleanly

Carries FDA 510(k) per vendor documentation. Independent attestation review is the buyer's responsibility before clinical deployment.

What the literature says

3 peer-reviewed studies indexed on PubMed evaluate Anumana in clinical contexts. The most relevant are shown below, ranked by editorial relevance score combining title match, study design, recency, and journal tier.

A Pragmatic Trial Evaluating the Impact of the Anumana Clinical Decision Support Tool for Guideline-Directed Management of Heart Failure (ACT-HF): Clinical trial design and methods. (opens in new tab)
Lopez-Jimenez F, Alger HM, Hackett SP, et al.· Am Heart J Plus· 2026
Heart failure with reduced ejection fraction (HFrEF) is progressive and pervasive. Guidelines provide evidence-based recommendations to manage HFrEF, yet adherence to Guideline Directed Medical Therapy (GDMT) is low. An opportunity exists to improve adherence by delivering actionable data, reducing clinician information overload, and enhancing patient care. A Pragmatic Trial Evaluating the Impact of the Anumana Clinical Decision Support Tool for Guideline-Directed Management of Heart Failure (ACT-HF) will evaluate a clinical decision support software (CDSS) that integrates in electronic healt…
Identification and risk stratification of coronary disease by artificial intelligence-enabled ECG. (opens in new tab)
Awasthi S, Sachdeva N, Gupta Y, et al.· EClinicalMedicine· 2023
Atherosclerotic cardiovascular disease (ASCVD) is the leading cause of death worldwide, driven primarily by coronary artery disease (CAD). ASCVD risk estimators such as the pooled cohort equations (PCE) facilitate risk stratification and primary prevention of ASCVD but their accuracy is still suboptimal. Using deep electronic health record data from 7,116,209 patients seen at 70+ hospitals and clinics across 5 states in the USA, we developed an artificial intelligence-based electrocardiogram analysis tool (ECG-AI) to detect CAD and assessed the additive value of ECG-AI-based ASCVD risk strati…

See all on PubMed (opens in new tab)