Ragaai Partners With Deephealth To Power Their Radiology AI Agents

2025-12-02 08:47:21

(MENAFN- EIN Presswire) EINPresswire/ -- RagaAI has announced today that its platforms are enabling DeepHealth, a global leader in AI-powered health informatics and wholly owned subsidiary of RadNet, Inc. (Nasdaq: RDNT), to shape a sustainable and responsible AI ecosystem. This includes building AI agents for workflow automation and Natural Language Agents monitoring. These AI agents, focused on optimizing Radiology workflows, aim to deliver gains in higher slot utilization and reduce operational delays

RagaAI's unified platforms - Prism for data quality, Canvas for building agents, and Catalyst for reliability and compliance are enabling end-to-end agent system automation in healthcare that is HIPAA-aligned and FDA-ready.

“At DeepHealth, we are reimagining how AI can automate operations safely, responsibly, and at enterprise scale to accelerate radiology, said Sham Shokka, Chief Operating and Technology Officer, DeepHealth.“Our collaboration with RagaAI enhances our ability to embed and deploy agentic intelligence with the aim of streamlining radiology workflows for simplified operations and enabling care teams to focus on what matters most-delivering the same high standard of care to every patient.”

“RagaAI is committed to bringing efficient and better healthcare through the rapid and responsible adoption of agentic AI. Through strategic collaboration with DeepHealth, RagaAI is enabling Agentic AI to improve the efficiencies of Radiology workflows. Using RagaAl platforms, healthcare teams can build and scale agents rapidly and ensure their reliability and compliance.” said Gaurav Agarwal, Founder & CEO, RagaAl

About RagaAI
Headquartered in the San Francisco Bay Area, RagaAI offers an enterprise platform to build and scale Healthcare AI Agents while following HIPAA and FDA guidelines. Its technology is used by radiology groups, hospitals, and imaging companies to ensure safe, reliable, and efficient deployment of operational and clinical AI. For more information, please visit:

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