Evom AI Secures $1M TIPS Funding to Build Cardiology AI Platform
Evom AI has been selected for Korea's Tech Incubator Program for Startups (TIPS) Deep Tech track, backed by the Ministry of SMEs and Startups. The selection includes 1.5 billion won (about $1.0 million) in government R&D support over three years. The goal: accelerate an AI platform for early detection and prediction of cardiovascular disease.
Founded in early 2025, the team includes medical AI veterans who previously led AI development, clinical research, regulatory, and commercialization at companies such as Lunit. Evom AI also secured seed funding from Klim Ventures in September 2025, adding private capital to the government-backed R&D runway.
Why this matters for developers
Cardiovascular disease is the top global cause of death, and earlier prediction changes outcomes and costs. That puts AI signal processing, multimodal modeling, and explainable decision support squarely in focus for healthcare builders. For context on disease burden, see the WHO overview.
What Evom AI is building
The company is assembling a large ECG-echocardiography paired dataset and applying its own automation stack for model development alongside an explainable AI framework. The ECG model is intended to detect subtle waveform signals that help clinicians make timely calls. The echocardiography AI automates dozens of measurements to support cardiac function assessment.
Next, Evom AI plans a multimodal approach that analyzes both ECG and echocardiography to estimate the risk of severe cardiac events before they occur. The intention is a shift from reactive treatment to proactive prevention inside routine workflows.
Technical angles to watch
- Paired data at scale: synchronization, label quality, and cross-vendor variability (ECG leads, echo probes, frame rates) will make or break generalization.
- Model development automation: reproducible pipelines, efficient search, and strong MLOps for versioning, monitoring, and rollback in clinical settings.
- Explainability: consistent, clinician-friendly attribution across ECG and echo, with clear failure modes and confidence reporting.
- Clinical integration: DICOM, HL7/FHIR, and PACS compatibility; on-device vs. server inference; throughput and latency at point of care.
- Validation and compliance: multi-site studies, device drift checks, and a path toward MFDS/CE/FDA submissions within an ISO 13485-aligned QMS.
Program context
The TIPS Deep Tech track is a private investment-led program supporting startups with strong tech and talent in strategic sectors. More on the ministry behind TIPS: Ministry of SMEs and Startups (Korea).
"Cardiovascular diseases remain the leading cause of death worldwide and continue to rise each year, making early prediction and preventive management more critical than ever," said Nam Hyeon-seob, CEO of Evom AI. "As a strong team backed by government R&D funding, we are well poised to lead the global market through groundbreaking cardiology AI."
What to expect next
Key milestones to look for: expansion of the paired dataset, external validation with multi-center studies, first regulatory submissions, and hospital pilots that prove workflow fit and measurable clinical impact. If those boxes get checked, broader deployment becomes a realistic next step.
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