Oxipit
Oxipit provides an AI‑powered platform that automatically analyzes medical images and generates structured radiology reports, integrating with existing PACS and RIS systems. By detecting and classifying pathologies across X‑ray, CT, and MRI studies and offering quantitative measurements and explainable visualizations, the solution helps hospitals and imaging centers improve diagnostic efficiency and reporting consistency.
- Artificial Intelligence
- Digital Health
- Healthcare Technology
- Software Only
Funding
Raised to date
$4.2MRaised 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
Radiology departments often face high workloads and variability in image interpretation, leading to delayed diagnoses and inconsistent reporting quality. Manual analysis of large volumes of imaging data can also increase the risk of missed findings and limit the scalability of advanced diagnostic services.
Solution
Oxipit offers an AI-powered platform that automatically analyzes medical images and generates structured radiology reports. The system integrates with existing PACS and RIS workflows, providing real-time assistance to radiologists by highlighting abnormalities, quantifying measurements, and suggesting diagnostic conclusions. By leveraging deep learning models trained on diverse imaging datasets, Oxipit delivers consistent, evidence‑based interpretations across modalities such as X‑ray, CT, and MRI. The platform presents results through an intuitive web interface and supports export to standard reporting formats, enabling clinicians to review AI insights alongside their own assessments and accelerate patient care.
Target Audience
Primary customers are hospitals, imaging centers, and radiology groups seeking to augment their diagnostic workflow and improve reporting efficiency.
Features
- Automated detection and classification of common pathologies in chest X‑rays, CT scans, and MRI studies
- Quantitative measurement tools (e.g., lesion size, volume) with AI‑derived accuracy
- Seamless integration with PACS/RIS via DICOM and HL7 interfaces
- Structured report generation with customizable templates and confidence scores
- Continuous model updates through federated learning to incorporate new data without compromising privacy
- Audit trail and explainability visualizations that show AI decision rationale