AWS and RapidAI Partner to Scale Deep Clinical AI for Hospitals Worldwide
News | Artificial Intelligence | December 01, 2025
RapidAI and Amazon Web Services (AWS) are deepening their collaboration to speed up global deployment of clinical-grade AI. The focus: co-development and go-to-market execution that pairs AWS's AI infrastructure with RapidAI's domain expertise and multimodal healthcare data.
Why this matters for healthcare leaders
The partnership centers on secure, scalable delivery of imaging AI that can run across complex environments. With multiple FDA clearances and a growing enterprise footprint, RapidAI is moving fast on clinically validated tools that fit into real-world workflows.
What's being featured at RSNA 2025
RapidAI will be in the AWS booth at RSNA 2025 with Rapid Edge Cloud, a cloud-native platform built on AWS that also supports on-prem operations. The goal is continuous, secure uptime in any clinical setting, from tertiary centers to regional hospitals.
- Deployed in 100+ countries with regional security and privacy controls
- Cloud scale with on-prem resilience for imaging-heavy environments
- Built for stringent compliance and data governance
"RapidAI is advancing the frontier of clinical AI by pairing domain-specific intelligence with scalable cloud infrastructure," said Dr. Rowland Illing, Global Chief Medical Officer and Director of Healthcare and Life Sciences, Amazon Web Services. "By building on AWS, they are helping hospitals accelerate AI-driven care delivery with confidence, resilience, and measurable clinical impact."
Co-development to speed innovation
AWS and RapidAI are co-developing advanced AI solutions and foundational model infrastructure. By combining AWS's AI pipelines with RapidAI's disease-specific expertise, the teams plan to deliver more adaptive, clinically validated AI that improves diagnostic precision, streamlines workflows, and broadens access across regions.
"AWS provides the trusted global infrastructure that allows RapidAI to deliver deep clinical AI at scale, securely, reliably, and without compromise," said Karim Karti, CEO of RapidAI. "Together, we're combining clinical depth with cloud scale, ensuring hospitals can use AI-driven insights no matter where they are in the world."
Clinical impact you can measure
Hospitals using deep clinical AI such as Lumina 3D are seeing tangible results. One Midwestern health system saved 24 minutes of CT technologist time per scan by automating 3D CTA head and neck reconstruction-freeing 72 hours per month and enabling five more scans per day. That translated into $61,000 per month in incremental imaging revenue across the system.
"With Lumina 3D, we've improved turnaround time and reduced the cognitive burden on our radiologists and technologists," said Raza Mushtaq, MD, neuroradiologist at the Barrow Neurological Institute. "Automation eliminates repetitive manual work, delivers consistent high-quality reconstructions, and gives our team the time and mental bandwidth to focus on interpretation and patient care. The operational and financial impact has been substantial."
From neurovascular to system-wide impact
RapidAI's clinically validated Rapid Enterprise Platform supports solutions such as Rapid Aneurysm, Lumina 3D, and Rapid Aortic. The company-long recognized for neurovascular deep clinical AI-is growing into orthopedic, cardiovascular, and oncology use cases. The shared aim: move from image to decision with fewer handoffs and clearer collaboration across teams.
What this means for your hospital IT and imaging teams
- Security and compliance baked in: Regional data residency, encryption, and privacy controls for cross-border deployments
- Cloud scale with local control: Keep scanners running and workflows intact even during network disruptions
- Faster time-to-value: Prebuilt pipelines to deploy, update, and validate models across enterprise environments
- Clinical credibility: AI grounded in disease-specific workflows with measurable operational and financial outcomes
Practical next steps
- Prioritize high-variance, high-volume imaging workflows (e.g., CTA head/neck) for early wins
- Map data flows with compliance and security teams to account for regional requirements
- Pilot at one site, capture baseline metrics (turnaround time, technologist minutes per scan, added throughput), then scale
- Engage radiology, IT, and operations leaders together to align ROI with staffing and scheduling
This integration builds on RapidAI's global momentum, multiple FDA clearances, and expanding enterprise deployments across health systems. For a deeper look at FDA policy on AI/ML in medical devices, visit the FDA's AI/ML SaMD resource.
For more information, visit RapidAI.
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