Day 1

By 2030, the role of traditional sales teams will be radically transformed—or even obsolete—thanks to the rise of Large Language Models (LLMs). These AI-powered tools are redefining how businesses connect with customers, blending advanced conversational capabilities with data-driven insights to streamline the entire sales process. This session will delve into the ways LLMs are automating lead generation, personalizing outreach at scale, and closing deals faster than ever, signaling the dawn of an AI-first era in sales. Join us to uncover how LLMs will shape a future where human sales efforts take a backseat to intelligent, automated systems.

Session will help you define the Platform features for a successful implementation of Ops for Data and identify the challenges

Discover how to create intelligent agents and multiagent systems using cutting-edge open-source technologies. This talk will explore various frameworks and best practices for building robust collaborative agents and attendees will gain insights into some real-world applications of multi-agent systems.

In this presentation, we will explore the current challenges facing the supply chain industry and discuss the critical importance of leveraging data-driven insights to modernize operations. We will delve into the role of data, highlighting key strategies such as data integration, real-time analytics, and predictive and prescriptive insights, alongside the transformative impact of advanced technologies like Generative AI. Additionally, we will examine architecture best practices from the industry, showcasing real-world examples of how organizations have successfully implemented these strategies to drive efficiency and resilience. Attendees will gain a comprehensive understanding of how to harness data to enhance supply chain operations, with concrete insights into effective architectural frameworks and future trends that will shape the supply chain landscape.

This session explores the new technologies and domain opportunities that are expanding at a rapid pace, like Robotics, XR (Mixed Reality), Neural Interfaces, Genetic Engineering, and many more.

This session explores how deep learning, particularly CNNs and advanced architectures, is transforming medical imaging. Drawing on research from IIT Hyderabad, it covers applications in detecting diseases through X-rays, MRIs, and CT scans, enhancing diagnostic accuracy. Key topics include challenges in data preparation, interpretability techniques to improve transparency, and how AI integrates into clinical workflows to support radiologists. Ethical considerations and future directions, such as privacy-preserving federated learning, highlight the responsible deployment of AI in healthcare.