India's Biggest GenAI Summit for developers

Even the most advanced AI assistant falls short of its potential without the right context. In this workshop, we will uncover how to transform a standard AI model into a truly agentic system by integrating multiple data sources—both structured and unstructured. Through real-world examples, we will build a conversational assistant that understands queries, incorporates essential organizational context, identifies the appropriate skill set, and provides accurate, actionable responses. We will also tackle the practical realities of deploying such systems in production, sharing proven strategies to overcome challenges and ensure accuracy, reliability, and scalability in real-world applications.

Dive into the world of multi-agent systems and learn how to build them from the ground up using Google's Gemini AI models. This hands-on workshop will guide you through essential design patterns and architectural components for creating robust, scalable multi-agent applications. Using a unified Gemini SDK compatible with both Google AI Studio and Vertex AI, we'll implement features like function calling, structured output, tool integration, and real-time web search to augment Gemini's capabilities. You'll gain practical experience by developing a research-focused multi-agent system that leverages these features, together with the ability to structure data output in Pydantic format, to generate an in-depth market analysis report for the Electric Vehicle (EV) industry. This workshop is ideal for developers and researchers seeking to master the art of building sophisticated AI-powered systems with Gemini.

In an era of global connectivity, organisations face the challenge of balancing scalability with compliance. This session explores how cloud computing and DevOps practices can help businesses establish a global presence while reducing operational costs and managing compliance in-house. Drawing on real-world examples, we’ll discuss how to eliminate the need for dedicated resources and optimise efficiency. Gain insights into leveraging cloud and DevOps to enhance global infrastructure while maintaining robust security and operational agility.

Generative AI is changing the game for digital marketing, offering new ways to engage with audiences and create personalized experiences. In this session, we’ll dive into how AI is helping brands generate dynamic content, automate tasks, and craft smarter marketing strategies. From AI-driven ad designs to tailored customer experiences, we’ll explore how this technology is enabling marketers to work faster, more efficiently, and more creatively. Through real-world examples, you’ll see firsthand how Generative AI is revolutionizing digital marketing, offering a powerful tool for driving results and connecting with customers on a deeper level.

The emergence of Agentic AI is ushering in a new era in workplace transformation, as generative AI moves beyond traditional support roles to become fully autonomous digital workers capable of independently analyzing, generating insights, and making complex decisions. Unlike earlier AI systems that relied on direct human commands, Agentic AI operates with a high degree of autonomy, taking initiative in completing tasks and managing workflows with minimal intervention. This capability not only reduces the administrative burden on human teams but also enhances the speed and accuracy of data-driven decision-making, positioning organizations to be more agile and competitive. Studies highlight the profound impact of this transition. For instance, a recent survey found that nearly 80% of companies integrating AI agents have seen a 30% increase in operational efficiency and a 25% reduction in repetitive tasks. According to McKinsey, organizations adopting generative AI in customer service experience a 20-40% improvement in response times and customer satisfaction. Additionally, Gartner projects that by 2030, Agentic AI will handle nearly 50% of routine enterprise tasks, enabling companies to redeploy human resources toward creative and strategic functions. The implications are vast. From intelligent document processing to conversational AI assistants that streamline customer interactions, Agentic AI is changing the landscape of industries like finance, healthcare, retail, and beyond. This shift not only drives productivity but fosters a workplace environment where employees can focus on higher-value contributions, innovation, and problem-solving. With Agentic AI at the forefront, workplaces are poised to evolve into hubs of collaboration where AI and human capabilities seamlessly integrate, redefining what’s possible in the future of work. At Vodex, We have been at the forefront of this transformation, pioneering solutions that bridge the gap between human-centric workflows and intelligent automation. Our global impact lies in fostering seamless integration of Agentic AI, which not only empowers businesses to scale but also ensures ethical, adaptable, and resilient implementations that respect the human experience at work. Through tailored approaches and scalable frameworks, Vodex has established itself as a key player in reimagining the modern workplace with Agentic AI.

AI will reshape industries by seamlessly combining precision with creativity, offering both analytical depth and innovative potential. Predictive AI and Generative AI in tandem can achieve optimal outcomes. This synergy can ensure more efficient, accurate, and scalable operations across industries like insurance, healthcare, and finance.

This session explores how the rise of AI—particularly Large Language Models (LLMs)—is poised to transform the way we design and build software systems. Traditional software architectures rely on predefined interfaces at both the front end (user interfaces) and the back end (API contracts). However, as AI advances in its ability to understand user intent and contextual data in real time, these static design paradigms are being challenged.

This workshop delves into the transformative applications of Large Language Models (LLMs) in the financial sector, showcasing their use in risk management, fraud detection, automated reporting, and personalized customer experiences. Participants will explore LLM architectures, real-world case studies, and hands-on techniques to fine-tune models for financial tasks. The session also addresses regulatory challenges, ethical considerations, and deployment best practices in this highly regulated industry. Ideal for data scientists and tech leaders, the workshop equips attendees with actionable insights and practical skills to harness LLMs, driving efficiency and innovation in financial workflows.

In a world where Web3 and Artificial Intelligence are driving the next wave of innovation, this session, "Building Crypto in the World of AI," dives into the real-world use cases of Web3 technologies. The speaker will explore how AI is reshaping blockchain applications, from decentralized finance (DeFi) to data ownership, digital identity, and governance in autonomous organizations. Gain insights into how these advancements are creating smarter, more secure, and scalable ecosystems, driving the adoption of decentralized technologies across industries.

Data is the backbone of Generative AI, yet traditional architectures struggle to meet the complex and dynamic demands of modern AI workflows. My talk will delve into cutting-edge data engineering approaches, including real-time streaming, distributed feature stores, and leveraging vector databases to handle the complexities of unstructured data. In addition, my talk will explore the critical roles of data management and governance in ensuring data quality, compliance, and security across the AI lifecycle. Attendees will gain valuable insights into the design and implementation of robust data and AI governance frameworks—critical for maintaining data accuracy, reliability, and accessibility while adhering to industry regulations and organizational policies. These frameworks are essential for enabling organizations to develop AI systems that are both high-performing and responsibly governed.

As developers, we constantly learn and find ways to resolve bugs in software through various methods. Initially, our sources of knowledge were books, peers, and college teachers. Over time, we turned to online trainers, platforms like Stack Overflow, and informative articles. As an online trainer (or YouTuber), I noticed that students often relied on us for guidance and problem-solving. However, with the advent of AI, students are now leveraging technology to resolve their issues and debug code independently. In this evolving landscape, I believe educators have an even greater role to play. Our focus should shift toward equipping students with the skills to effectively utilize AI tools while fostering a deeper understanding of the principles behind them.

Among a lot of noise and news around data & AI, it would be pragmatic to look at what are the real solutions for real people. At Chargeup, we created last-mile Mobility solutions for EV drivers using data captured through IOT, and urn analysis on Assets and People and thus created unique AI/ML models for last-mile EV drivers. Watch this space for listening to "Real Solutions for Real People Solving Real World Problems.

To effectively measure AI product performance, it is essential to establish clear metrics that reflect the desired outcomes. Key performance indicators (KPIs) should encompass accuracy, efficiency, user satisfaction, and overall impact. Continuous monitoring and evaluation against these KPIs will help identify areas for improvement and optimize functionality. Furthermore, incorporating user feedback can enhance product relevance and adaptability. Ultimately, a comprehensive performance measurement strategy will drive the success and evolution of AI products.

This talk explores the transformative role of agentic AI in the finance sector, highlighting its impact on trading, risk management, fraud detection, and personalized financial services. We will discuss how AI systems analyze vast datasets to enhance decision-making and improve operational efficiency, while also addressing the ethical considerations and challenges posed by their deployment. As financial institutions increasingly rely on AI-driven solutions, understanding both the opportunities and risks is crucial for navigating this rapidly evolving landscape. Join us to discover how agentic AI is shaping the future of finance and what it means for businesses and consumers alike.

In this talk, I will provide an overview of quantum algorithms, focusing on key areas like Quantum Machine Learning (QML), Quantum Optimization (QO), and Quantum Simulation (QSim). I'll also introduce Bloq Quantum's role in simplifying quantum adoption and discuss the broader quantum software landscape. We'll explore the leading quantum cloud platforms, including AWS, Azure, GCP, and IBM, comparing their offerings and the impact of cloud on the future of quantum computing.