b-rayZ develops AI software for the standardization and automation of breast imaging workflows, enhancing diagnostic accuracy and efficiency in radiology. The platform addresses issues of misdiagnosis and workflow inefficiencies by providing real-time results and quality assurance throughout the diagnostic process.
Funding
$4.1M 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
Breast imaging workflows often suffer from inefficiencies and inconsistencies, leading to potential misdiagnoses and increased workloads for radiologists and technicians. Existing solutions may lack the adaptability to integrate seamlessly with diverse IT infrastructures and imaging devices, hindering standardization and optimal image quality.
Solution
b-rayZ offers an AI-powered platform designed to standardize and automate breast imaging workflows, enhancing diagnostic accuracy and streamlining operations for patients, technicians, radiologists, and clinical managers. The platform's core technology, DANAI, is an adaptive AI framework that evolves over time, learning from real-world applications and radiologist feedback to ensure high accuracy in image classification and personalized diagnostics. By integrating seamlessly into existing IT infrastructures and device manufacturers, b-rayZ provides real-time results, automates image quality assessments, and facilitates consistent, reliable diagnostics across different imaging modalities. The b-rayZ suite supports women through the entire diagnostic journey, offering real-time BI-RADS ACR and Image Quality classifications.
Target Audience
The primary target audience includes radiologists, medical technicians, and clinical managers in hospitals, radiology clinics, and screening programs focused on improving the efficiency and accuracy of breast cancer diagnostics.
Features
- AI-driven standardization and automation of breast imaging workflows
- DANAI technology: adaptive AI that learns from clinical data and radiologist input
- Real-time image quality assessment and feedback for medical technicians
- Automated BI-RADS ACR classification
- Integration with existing IT infrastructure and various device manufacturers
- Streamlined diagnostic process for increased efficiency and reduced workloads
- Multi-modality product pipeline that follows the entire patient journey