Introduction of the Speaker

It is a pleasure to introduce, Er. Rajeshwar Agrawal, an alumni 2010-14 (B. Tech, CSE),  a Senior Software Engineer and system architect with over a decade of hands-on industry experience in designing and delivering large-scale, AI-ready data platforms and intelligent backend systems.

Mr. Agrawal is currently associated with SteelEye, where he plays a critical role in architecting high-throughput, cloud-native data platforms for trade and communication surveillance. These systems process millions of records daily, combining automation with human-in-the-loop oversight to support regulatory compliance, operational transparency, and informed decision-making. His work exemplifies Industry 5.0 principles, where advanced digital systems enhance human judgment rather than replacing it.

Previously, at Motional, a leader in autonomous vehicle technology, Mr. Agrawal contributed to the development of scalable, serverless backend systems that enabled access to complex data pipelines, KPIs, and test-ride intelligence—supporting engineers and researchers working on safety-critical AI systems. Earlier in his career, at Works Applications, he helped build mission-critical microservices architectures capable of handling thousands of transactions per second, demonstrating deep expertise in resilient, distributed system design.

Across his career, Mr. Agrawal has worked at the intersection of data engineering, cloud infrastructure, DevOps, and AI-enabled systems, with a strong focus on cost-efficient architectures, observability, and scalability. His background spans fintech, autonomous systems, and enterprise platforms, giving him a unique cross-industry perspective on how symbiotic AI systems can be operationalized at scale.

Mr. Agrawal holds a Bachelor’s degree in Computer Science from IIIT Jabalpur, and brings a strong practitioner’s viewpoint on building the digital foundations required for human-centric, trustworthy AI in Industry 5.0.

We are delighted to have him share his insights today on robust data engineering, cloud platforms, and AI-ready architectures empower humans to make better, faster decisions in complex systems.

Title

Case Studies on Symbiotic AI 

Abstract

To be updated soon..