Infervision provides AI-driven imaging analysis tools that automatically detect and triage abnormalities in CT, X‑ray, and CTA scans, delivering real‑time alerts and quantitative assessments that integrate with existing PACS, RIS, and EMR systems. Its suite includes 3D reconstruction for surgical planning, longitudinal patient monitoring, and platforms for research and custom AI model deployment, helping radiology and surgical teams improve diagnostic accuracy and workflow efficiency.
Funding
$140M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Radiologists and surgeons often rely on manual interpretation of CT, X‑ray, and CTA scans, which can be time‑consuming, subject to variability, and may miss subtle abnormalities, leading to delayed diagnoses and suboptimal treatment planning.
Solution
Infervision offers a suite of AI‑powered imaging analysis tools that automatically detect and triage abnormalities across multiple modalities, including lung nodules, chest fractures, coronary artery stenosis, brain hemorrhage, and pneumonia. The InferRead® products provide real‑time alerts and quantitative assessments that integrate seamlessly into existing PACS and hospital workflows, reducing the need for extensive manual review. InferOperate® modules generate 3D reconstructions for thoracic, liver, and urological surgeries, supporting precise pre‑operative planning. InferCare® enables longitudinal patient management by tracking imaging changes over time, while InferScholar® and InferMatrix provide platforms for AI‑driven research and custom application development. Together, these solutions aim to improve diagnostic accuracy, accelerate clinical decision‑making, and enhance overall operational efficiency in healthcare facilities.
Target Audience
Primary customers are radiology departments, surgical teams, and clinical research groups in hospitals and large imaging centers that require AI assistance for diagnosis, treatment planning, and patient management.
Features
- Deep learning models for detection of specific pathologies in CT, X‑ray, and CTA scans (e.g., lung nodules, coronary stenosis, brain hemorrhage)
- Automated triage and prioritization of abnormal studies with confidence scores
- Seamless integration with PACS, RIS, and EMR systems via standard DICOM and API interfaces
- 3D reconstruction tools for thoracic, hepatic, and urological surgical planning
- Longitudinal imaging follow‑up and change detection through InferCare®
- Research platform (InferScholar®) and extensible AI application framework (InferMatrix) for custom model deployment
- Cloud‑based analytics pipeline ensuring secure data transmission and storage
- FDA‑cleared modules for clinical use, supporting regulatory compliance