Cardiomatics
Financials
Estimates*
EUR | 2017 | 2018 | 2019 | 2020 | 2021 | 2022 | 2023 |
---|---|---|---|---|---|---|---|
Revenues | <1m | <1m | <1m | <1m | <1m | - | - |
% growth | - | 15 % | 86 % | (24 %) | 15 % | - | - |
EBITDA | <1m | <1m | (<1m) | <1m | (<1m) | - | - |
% EBITDA margin | 23 % | 2 % | (10 %) | 15 % | (61 %) | - | - |
Profit | <1m | (<1m) | (<1m) | <1m | (<1m) | (1.0m) | (<1m) |
% profit margin | 19 % | - | (15 %) | 7 % | (67 %) | - | - |
Source: Dealroom estimates
Date | Investors | Amount | Round |
---|---|---|---|
- | N/A | - | |
$640k | Grant | ||
$300k | Seed | ||
$2.2m | Seed | ||
$1.0m | Grant | ||
Total Funding | AUD6.4m |
Related Content
Recent News about Cardiomatics
EditCardiomatics is a cloud-based AI platform specializing in the analysis of electrocardiograms (ECGs). The company serves healthcare providers, including cardiologists and hospitals, by offering an advanced tool that converts raw ECG signals into detailed, actionable reports. Operating in the cardiac diagnostics market, Cardiomatics leverages machine learning algorithms to facilitate and expedite the diagnosis of arrhythmias, a condition characterized by irregular heartbeats. The business model is primarily subscription-based, where clients pay for access to the platform and its analytical capabilities. Revenue is generated through these subscriptions, as well as potential one-time fees for specific analyses or trials. The platform is certified as a Medical Device Class IIa, ensuring compliance with stringent medical standards. Cardiomatics' technology is particularly valuable in clinical settings, where it significantly reduces the time required for ECG analysis compared to traditional Holter software. This efficiency is crucial for uninterrupted operations, even during challenging times like the COVID-19 pandemic. The company’s user-friendly web-based interface allows for quick uploading of ECG data and rapid generation of comprehensive reports, making it an indispensable tool for modern cardiology practices.
Keywords: ECG analysis, cloud AI, arrhythmia diagnosis, cardiology, machine learning, medical device, subscription model, healthcare, cardiac diagnostics, clinical efficiency.