AI-powered PACS, EMR, and HIS integration for hospitals — connecting every department, automating radiology workflows, reducing turnaround time, and improving diagnostic accuracy from scan to report.
Accelerate radiology reporting with AI-driven DICOM image analysis — reduce costs, increase throughput, and deliver faster, more accurate diagnostic imaging results.
AI-powered medical imaging integration for insurers — automate insurance claims processing, detect fraud with intelligent data analysis, and make faster, evidence-based coverage decisions.
Teleradiology reporting platform — cloud-based DICOM viewer enabling remote radiologists to report across multiple centers, anytime, from any device.
RadpicsAI Combines AI-Powered, cloud infrastructure and healthcare expertise to improve diagnostic access and reporting.
RadpicsAI leverages artificial intelligence and cloud infrastructure to streamline radiology workflows, enhance diagnostic imaging accuracy, and enable seamless medical knowledge sharing across healthcare networks.
Our mission is to equip radiologists, hospital administrators, and diagnostic center teams with an intuitive, AI-driven PACS and DICOM platform that accelerates reporting, eliminates errors, and expands access to quality diagnostics.
RadpicsAI was found to solve a critical gap in healthcare imaging: slow, fragmented, and inaccessible radiology reporting across hospitals and diagnostic centers. We built an AI-powered PACS platform that unifies DICOM image viewing, clinical decision support, and teleradiology reporting — helping clinicians work faster, report smarter, and deliver better patient outcomes.
Cloud-based PACS software for hospitals. Automates radiology reporting, case allocation, and RIS PACS integration — all in one platform.
Connects EMR and radiology software for seamless hospital workflow. Automate appointments, patient records, and clinic scheduling for doctors and receptionists.
Centralized, secure storage for EMR reports and patient data — HIPAA-compliant, HL7-enabled, with built-in HIS integration. for hospitals and diagnostic centers across the world.
View CT, MRI, X-ray & Ultrasound DICOM images on any device — browser or mobile app. Powered by MPR, annotations, and AI-assisted radiology insights.
Secure video consultations for every healthcare need — from radiology second opinions and specialist referrals to Doctor consultations, all integrated with your PACS, EMR, and hospital workflow.
Track essential obstetric imaging stages with a compact, scan-ready decision support interface.
Early Obs: Early assessment
NT Scan: Nuchal translucency screening
Growth Scan: Fetal growth monitoring
Anomaly Scan: Detailed fetal anatomy assessment
Growth Scan: Continued fetal growth monitoring
Obs Doppler: Blood flow and growth evaluation
Breast Cancer Risk Assessment: The BI-RADS calculator helps assess the risk of malignancy in breast lesions based on mammography, ultrasound, and MRI findings.
Treatment and Follow-Up Planning: It aids in standardizing breast cancer diagnosis and follow-up protocols.
Thyroid Nodule Evaluation: The TIRADS calculator classifies thyroid nodules based on ultrasound characteristics.
Clinical Decision Support: It assists in biopsy, follow-up imaging, or monitoring decisions.
Ovarian and Adnexal Lesion Assessment: The OI-RADS calculator categorizes ovarian and adnexal lesions on imaging.
Guides Treatment and Surveillance: It helps clinicians determine next steps for safe management.
BCLC Staging System: The Barcelona Clinic Liver Cancer system assesses HCC stage.
Personalized Treatment Guidance: BCLC guides treatment decisions based on cancer stage and patient condition.
Automates workflows, reducing reporting turnaround times by up to 40% and operational costs by 20-30%.
Built for growth, enabling networks to handle up to 10x more cases as operations expands.
Expands access to advanced diagnostics, potentially reaching 80% more underserved areas through remote reporting.
Enhances stakeholder interaction, improving data- sharing efficiency by 50% and reducing manual errors.
