Day 1

In an increasingly competitive and data-rich landscape, Consumer Packaged Goods (CPG) companies are investing heavily in analytics, AI, and digital transformation—yet many still struggle to translate insights into impactful business outcomes. This session explores Decision Intelligence as the critical missing link that bridges data, analytics, and real-world decision-making.
We will delve into how Decision Intelligence frameworks enable organizations to move beyond dashboards and predictions toward structured, repeatable, and scalable decision processes. By integrating data, context, human judgment, and AI-driven recommendations, CPG leaders can optimize pricing, promotions, supply chains, and demand planning with greater precision and speed.

Through practical examples and industry use cases, the session will highlight how embedding Decision Intelligence into everyday workflows can unlock measurable improvements in performance, agility, and ROI—helping CPG organizations turn complexity into a competitive advantage.

Everyone is building agents. Almost no one is running them in production.

Eighteen months ago, one of our agents changed a VLAN configuration on a network device during a controlled proof of concept. It put an access point on the wrong VLAN, isolating every client connected to it. The agent completed the task successfully. No error was thrown. No alert fired. From the system’s perspective—everything was fine.

That incident taught us more about production-grade agentic AI than any benchmark or architecture paper. It revealed four failure zones that most enterprise AI teams have not yet engineered for: Silent Failure, Black Box Decisions, Permission Explosion, and Runaway Execution.

This session moves beyond agent architecture theory to the operational discipline required to run autonomous systems inside mission-critical enterprise environments—the kind where SLAs are real, permissions matter, and a wrong decision has consequences. We will walk through the 4-Layer Enterprise Agent Stack, a framework built on the principle that “The user is all”—ensuring agent permissions never exceed what the human behind the request is authorized to do.

The future of enterprise AI will not be decided by model intelligence. It will be decided by operational discipline.

Building an agent can be done quickly. Building an agent that holds up in production, under time pressure, with operational reliability – now, that’s the hard part.

In this talk, an AI researcher from Millennium will explain a practical engineering playbook for deploying agents into high-stakes buy-side workflows: research, monitoring, operations, and reporting processes.

This talk will go beyond buzzwords to show how to build a production-grade agent: composing proven patterns (with tool-chaining, reflection, human-in-the-loop, and selective multi-agent design) into systems that are constrained, observable and governable. This session will highlight the failure modes that tutorials omit, and the design decisions that prevent them.

BharatGen represents a new paradigm in building AI systems that are sovereign, inclusive, and purpose-built for India’s diverse linguistic and cultural landscape. This session explores how frugally scalable multilingual and multimodal AI models can be developed to serve Bharat at scale, balancing technological advancement with accessibility and efficiency. It will highlight the principles behind shared national AI infrastructure, enabling collaboration across academia, industry, and government to create AI that understands and serves India’s many languages and modalities. Attendees will gain insights into the opportunities, challenges, and impact of building sovereign AI capabilities that empower innovation while ensuring that AI development remains accessible, affordable, and aligned with the needs of Bharat.

As AI agents evolve from experimental prototypes to real-world production systems, enterprises are realizing that model capability alone is not enough. The true challenge lies in how agents manage, retrieve, and retain information across complex, long-running workflows. Getting this right is often the difference between an impressive demo and a system that consistently delivers value.
Building effective agentic AI requires a strong approach to context and memory. Developers must understand how different memory types such as in-context, external, episodic, and semantic work together, and when to use each. Techniques like Retrieval-Augmented Generation (RAG) help bridge knowledge gaps, while thoughtful design ensures agents can retain and use information across sessions.
Join us for this Tech Talk where Sanketh and Anshul will break down how context and memory shape intelligent agents. Walk away with a practical framework for building AI agents that remember, reason, and scale reliably.

The rapid expansion of the global space economy is generating unprecedented volumes of data and increasingly complex operational challenges. Traditional AI systems have largely focused on narrow tasks such as image classification or anomaly detection.

However, the next frontier lies in agentic AI systems that can perceive, reason, and act autonomously across multiple components of the space ecosystem.

This talk explores how agentic AI can enable a new generation of autonomous space capabilities, spanning satellite Earth observation, robotic spacecraft operations, and intelligent ground infrastructure.

We will discuss AI agentic workflow examples that detect vehicles and strategic assets from satellite imagery, support autonomous robotic docking and inspection, and optimize ground station networks for efficient satellite communications.

As AI disrupts current Architectures, we need certain principles to architect applications appropriately & harness the full potential of AI. The sessions explain the Guiding Principles for implementing multi-agentic applications and provide a technical breakdown of those principles, using examples from Snowflake Cortex Agents & Platform.