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Special Presentation by Rahul Reddy Hanumanthgari

Hosted by the Expert Tech Talks (IEEE Philadelphia Section)

Date/Time: Monday, 4 May 2026 @ 7 PM Eastern Time

Topic:

Building AI-Native Enterprise and Healthcare Systems

Abstract:

Organizations across enterprise and healthcare are investing heavily in AI, yet only a small number are successfully turning pilots into systems that deliver real, lasting value. The challenge is no longer just building models — it is identifying the right use cases, deciding where AI is truly needed, and designing systems that are trustworthy, scalable, observable, and aligned with operational workflows. In high-stakes environments such as healthcare, these requirements become even more critical, where quality, compliance, human oversight, and reliability directly shape adoption and impact. Agentic AI, orchestration frameworks, evaluation-driven development, and human-in-the-loop design are creating a new path from experimentation to transformation. In this presentation, we explore how organizations can evaluate AI opportunities, choose the right tools and architectural foundations, and build trusted agentic systems that move beyond isolated experiments into production-ready capabilities for enterprise and healthcare environments.

Speaker:

Rahul Reddy is an AI Engineering Leader and Applied AI Researcher focused on building trustworthy, production-ready AI systems for enterprise and healthcare environments. His work spans agentic AI, enterprise architecture, evaluation-driven development, automation, and applied research, with a strong emphasis on high-impact and regulated settings. Rahul is particularly interested in how organizations can move from fragmented AI experimentation to scalable systems that are governed, observable, and aligned with real business and clinical workflows. His areas of focus include agentic systems, enterprise AI platforms, LLM evaluation, orchestration patterns, and trustworthy AI deployment. He brings a practical perspective on translating technical depth into strategic impact and helping organizations prepare for an AI-native future.

 


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  • Co-sponsored by IEEE Future Networks AI/ML Working Group

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Rahul of Lab Corp

Topic:

Building AI-Native Enterprise and Healthcare Systems

Abstract:

Organizations across enterprise and healthcare are investing heavily in AI, yet only a small number are successfully turning pilots into systems that deliver real, lasting value. The challenge is no longer just building models — it is identifying the right use cases, deciding where AI is truly needed, and designing systems that are trustworthy, scalable, observable, and aligned with operational workflows. In high-stakes environments such as healthcare, these requirements become even more critical, where quality, compliance, human oversight, and reliability directly shape adoption and impact. Agentic AI, orchestration frameworks, evaluation-driven development, and human-in-the-loop design are creating a new path from experimentation to transformation. In this presentation, we explore how organizations can evaluate AI opportunities, choose the right tools and architectural foundations, and build trusted agentic systems that move beyond isolated experiments into production-ready capabilities for enterprise and healthcare environments.

Biography:

Rahul Reddy is an AI Engineering Leader and Applied AI Researcher focused on building trustworthy, production-ready AI systems for enterprise and healthcare environments. His work spans agentic AI, enterprise architecture, evaluation-driven development, automation, and applied research, with a strong emphasis on high-impact and regulated settings. Rahul is particularly interested in how organizations can move from fragmented AI experimentation to scalable systems that are governed, observable, and aligned with real business and clinical workflows. His areas of focus include agentic systems, enterprise AI platforms, LLM evaluation, orchestration patterns, and trustworthy AI deployment. He brings a practical perspective on translating technical depth into strategic impact and helping organizations prepare for an AI-native future.

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