Enterprise Agentic AI at the Edge: Memory, Reasoning, and Physical Intelligence
For the past several years, enterprise AI has largely been defined by a simple assumption: intelligence lives in the cloud.
But what happens when AI needs to operate where connectivity is limited, latency matters, privacy is critical, or decisions must be made in real time?
As organizations explore AI-powered devices, autonomous systems, robotics, industrial operations, and next-generation customer experiences, a new architecture is emerging—one where reasoning, memory, and decision-making move closer to the edge.
Join the Capgemini Applied Innovation Exchange for a discussion on the future of Agentic AI beyond the datacenter. Together with leaders from Qualcomm, Arduino, and Moorcheh.ai, we'll explore how advances in edge computing, local inference, vector search, and persistent memory are enabling intelligent systems to operate directly on devices while maintaining context, autonomy, and responsiveness.
The evening will combine enterprise perspectives, technical deep dives, and live demonstrations showcasing what becomes possible when AI systems can remember, reason, and act without constant reliance on cloud infrastructure.
Whether you're building AI products, exploring physical AI, evaluating agent architectures, or thinking about the next generation of enterprise systems, this session will provide a practical look at where the technology is heading—and what challenges still need to be solved.
Agenda
5:30 PM – 6:00 PM
Check-in, food, and networking
6:00 PM – 6:15 PM
Opening Perspective: The Next Frontier of Enterprise AI
Capgemini Applied Innovation Exchange & AICamp
A discussion on the evolution of enterprise AI architectures and why memory, autonomy, and edge intelligence are becoming critical design considerations as organizations move from AI assistants to AI agents and physical AI systems.
6:15 PM – 8:00 PM
Technical Talks & Q&A
8:00 PM – 8:30 PM
Open discussion, networking, and closing
Featured Sessions
A Technical Walkthrough of the Arduino UNO Q Platform
Arduino
An overview of the hardware, software stack, and optimization strategies that enable local AI workloads on highly constrained devices.
The Moor Edge: Information-Theoretic Search and Agentic Memory on Arduino UNO Q
Dr. Majid Fekri, CTO & Co-Founder, Moorcheh.ai
A live demonstration of local semantic search, persistent memory, and on-device AI running entirely offline.
Gen Edge AI: Reasoning, Agentic Memory, and Physical Intelligence
Tara Khani, CEO & Co-Founder, Moorcheh.ai
An exploration of how memory systems may become a foundational layer for autonomous agents, physical AI, and next-generation intelligent applications.
Hosted by the Capgemini Applied Innovation Exchange in collaboration with AICamp.