- ECG-AI for earlier cardiac detection
- Targets cardiology needs rather than a generic suite
- Scales to organization-wide healthcare rollouts
- Three FDA-cleared cardiac algorithms available
- Processing remains within customer infrastructure
- Integrates with existing EHR workflows
- Medicare outpatient reimbursement available for LEF
- LEF validated across diverse patient populations
Anumana
ECG AI for earlier cardiac detection
SF7.28
SF Score editorial score across features, ease, and value, based on public reviews and product research. Learn more →
Support coronary artery disease evaluationCardiology and health system programs
Support coronary artery disease evaluationCardiology and health system programs
Best for
Cardiology and health system programs
Pricing
Custom
Free plan
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SoftFinders Score
7.28 / 10
Overview
What is Anumana?
Anumana is an AI cardiology platform for cardiology and health system programs, developing ECG algorithms that flag cardiac conditions to support earlier clinician detection.
- Clinical role: It supports cardiac imaging and risk stratification rather than autonomous cardiology, so cardiologist review remains essential for interpretation, treatment, and reporting decisions.
- Best-fit environment: Cardiology and health system programs may benefit most when ECG-AI fits established diagnostic workflows.
- Evaluation priorities: Buyers should confirm regulatory clearance scope, imaging modality fit, reporting integration, and clinical validation evidence before rollout.
- Commercial model: Pricing is sales-led and scoped per buyer rather than publicly posted, making deployment scope and support purchasing considerations.
Anumana is best evaluated through a pilot that tests ECG-AI workflow fit, clearance scope, and cardiologist oversight before adoption.
KEY FEATURES
What you get out of the box
Image Analysis
AI analysis of cardiac imaging studies
Risk Stratification
Stratifies cardiovascular risk from inputs
FFR CT Models
Personalized coronary flow models from CT
Plaque Analytics
Quantifies plaque burden and composition
USE CASES
Where teams put it to work
Support coronary artery disease evaluation
Quantify plaque burden from coronary CT
Stratify cardiac risk across patient panels
Analyze echocardiograms with AI
Bridge imaging and cardiology pathways
Standardize cardiac imaging reporting
Editorial Take
What we like, and what to verify
- Clearance scope varies by algorithm
- Cardiologist confirmation required on findings
- Pricing is sales-led and needs scoping upfront
- Algorithms do not replace clinician diagnosis
- LEF excludes paced-rhythm ECGs
- PH excludes patients with implanted pacemakers
- LEF is not intended for monitoring
Screenshots
A look inside
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USER REVIEWS
Anumana Reviews
Published user reviews are moderated and kept separate from the SoftFinders Score.
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Reviews from real users will appear here once published.
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