VivaQuant

VivaQuant

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Private Company

Total funding raised: $19M

Overview

Founded in 2010 and headquartered in St. Paul, Minnesota, VivaQuant operates at the intersection of digital health and diagnostics with a specialized focus on cardiac arrhythmia detection. The company's core offering is its proprietary ECG analysis software platform, which utilizes advanced signal processing and machine learning algorithms to identify and characterize arrhythmias from ECG data. This technology targets a significant unmet need for more accurate, automated, and efficient analysis tools in cardiology, aiming to reduce diagnostic errors and clinician workload. As a private company, VivaQuant likely generates early revenue through software licensing and partnerships with medical device manufacturers and healthcare providers.

Cardiology

Technology Platform

Proprietary ECG analysis software platform utilizing advanced signal processing and machine learning algorithms for automated detection and characterization of cardiac arrhythmias.

Funding History

4
Total raised:$19M
Debt$2.5M
Series B$10M
Series A$5M
Seed$1.5M

Opportunities

The growing global burden of cardiovascular disease and the expansion of remote patient monitoring create a large and expanding market for automated ECG analysis.
The need for healthcare efficiency drives demand for software that can reduce manual review time and costs in diagnostic labs.

Risk Factors

Intense competition from both large medtech conglomerates and nimble AI startups threatens market share.
The business model is heavily reliant on securing OEM partnerships with device manufacturers, creating commercialization and dependency risks.

Competitive Landscape

VivaQuant competes in a crowded field that includes large, integrated device companies (e.g., GE Healthcare, Philips, Boston Scientific) with their own analysis software, as well as specialized digital health companies (e.g., iRhythm, Bardy Diagnostics) and pure-play AI/software startups. Differentiation is based on algorithmic accuracy, workflow integration, and the breadth of arrhythmias detected.