HALL 1 (Main) - Keynotes / Tech Talks

Developing generative AI-powered voice agents is typically a complex and time-consuming process, often taking weeks or even months. This session introduces a groundbreaking platform that shatters those barriers, enabling you to deploy sophisticated voice agents in just 24 hours. Discover how this revolutionary technology empowers you to rapidly create and customize intelligent voice experiences, transforming the way you interact with your customers.

Generative AI is transforming life insurance customer service by boosting efficiency and personalisation. From intelligent virtual assistants assisting customers 24*7 to seamless claims settlement process, AI is everywhere. It analyzes vast customer data to offer personalized policy recommendations, increasing satisfaction and loyalty. Additionally, Generative AI enhances risk assessment accuracy, simplifies underwriting processes, and produces engaging content. Despite challenges in regulatory compliance and data security, AI strengthens compliance measures and safeguards data, heralding a transformative impact on the industry.

Integrating LLMs into workflows and interfaces can really enhance customer experience. However, achieving impactful outcomes is not an overnight transformation. Drawing from examples of our adoption process, this session will walk through the iterative journey of enhancing customer-facing interfaces, support agent tools & internal processes using LLMs.
The emphasis will be on:
Starting small and scaling thoughtfully.
Learning from each phase of implementation.
Continuously refining based on user feedback and performance metrics.

As AI becomes increasingly crucial to enterprise success, we see companies moving deeper into a technological frontier that promises both opportunity and risks. The advent of generative AI has driven a surge in AI use cases throughout organizations. So, how are companies preparing—or not preparing—to keep pace with this rapidly evolving technology and avoid unintended consequences, both known and unknown?

Join the session to get answers on below:

1. Who are the executives representing organizations with larger AI governance budgets?
2. Do organizational investments in AI governance reflect a sense of urgency?
3. How many new AI models are in the enterprise forecast?
4. What kinds of AI tools and frameworks are organizations using?
5. Are respondents confident that their AI capabilities can meet the challenges ahead?
6. Which AI risks and regulations worry enterprises the most? 7. Who owns organizations’ AI governance?

Generative AI (GenAI) is revolutionizing software development and business operations, driving unprecedented productivity and innovation. In software development, GenAI is automating coding, testing, and optimization processes, accelerating development cycles and reducing technical debt. It enhances developer productivity by 20-50% through automated code generation and intelligent debugging, allowing professionals to focus on complex problem-solving. For businesses, GenAI is transforming operations through enhanced natural language processing, multimodal AI, and personalized customer experiences. The economic impact is substantial, with GenAI projected to contribute $6.1 to $7.9 trillion annually to the global economy. Despite challenges like potential job displacement, GenAI is creating new opportunities, with 97 million new jobs projected by 2025, reshaping industries and unlocking new frontiers of innovation.

This talk will explore how GenAI is not just an incremental advancement, but a paradigm shift that is redefining the very nature of software development and business operations, unlocking new frontiers of possibility in the digital age.

Large Language Models (LLMs), trained on extensive internet-scale datasets, demonstrate exceptional performance across diverse tasks. Yet, they often fall short when it comes to grasping the unique nuances of organizational data. As a result, standard LLMs frequently require human intervention to deliver accurate, business-specific insights.

Join us for this Tech Talk as we dive into the world of LLMs. Explore the challenges LLMs face with business-specific contexts and how we can make them more effective. Discover strategies for integrating organizational context into models, examine how LLMs utilize this enhanced information, and uncover its transformative impact on the accuracy and specificity of their responses.

As organizations increasingly embrace AI to drive actionable insights and automate workflows, the initial excitement around the technology gives way to a focus on delivering tangible value. This shift has placed the spotlight on deploying Large Language Model (LLM) applications in production environments.

MathCo’s experience across diverse use cases has shown that a successful AI strategy requires more than cutting-edge foundational models. It demands a strong foundation built on high-quality data, thoughtful design, business context, rigorous testing, and effective change management.

In this session, Sourav Banerjee will explore the essential building blocks of enterprise assistants, with compelling examples from the healthcare and consumer packaged goods (CPG) industries. He will delve into their evolution from prototypes to production, uncovering the challenges and strategies to overcome them.

With AI applications, infrastructure, and tools getting rolled out at scale, it is important that we focus on the security and privacy around building, deploying, using and governing these applications. My talk will focus on both the technical information security aspects- (vulnerabilities in AI applications and associated tech stacks, treatment/mitigation strategies, proactive, detective and reactive security engineering aspects) and also from the GRC- governance, risk, compliance/legal aspects of both the security and privacy elements.

This talk explores the strategies and best practices for designing and deploying data pipelines at scale. It will delve into how these pipelines are structured to handle large volumes of data efficiently and ensure seamless data flow across systems. By examining real-world examples, the session will demonstrate how robust data pipelines contribute to enhancing the functionality, performance, and user experience of software products. Attendees will gain insights into the tools, techniques, and considerations necessary to build scalable and reliable data pipelines that drive product innovation and business value.

Edge computing is revolutionizing earth observation (EO) by enabling satellites to process data directly in orbit, reducing reliance on ground stations for time-sensitive applications. This talk will highlight the benefits of edge computing for earth observation, such as reduced data transfer costs, faster response times in critical scenarios like disaster management, and real-time insights for sectors like agriculture and defence.

In September 2023 KaleidEO demonstrated on-orbit processing on EO satellites, showcasing real-time analytics capabilities like change detection and applications for vegetation, forestry and environmental monitoring. By enabling instantaneous data processing, edge computing ensures that actionable intelligence reaches decision-makers without delay, fostering more effective responses to natural disasters, better resource management, and stronger national security.

The edge computing innovation for EO marks an important evolution in the traditional approach, unlocking unprecedented potential for near real-time, data-driven, diversified applications from space.