DAY 1 | FREE TRACK
Edge Computing and AIoT Driving Real-Time Intelligence
09:45 - 10:00
Chairperson’s Opening Remark
Chairperson’s welcome and opening remarks
10:00 - 10:30
Presentation: Reimagining Data, Decisions, and Speed with Edge Computing
Edge computing is redefining how organizations move from data to action. This session will explore how pushing intelligence closer to where data is created accelerates decision cycles, improves responsiveness, and unlocks new operational capabilities. Real-world examples will illustrate how enterprises are benefitting.
10:30 - 11:00
Panel Discussion: Scaling Edge Deployments With Lessons from Real-World IoT Rollouts
This panel brings together leaders who have navigated the complexities of deploying IoT and edge systems at scale. They’ll share hard-won lessons, unpack what went right (and what didn’t), and outline the strategies that helped them achieve measurable results. Attendees will walk away with field-tested insights they can apply immediately.
11:00 - 11:30
Presentation: Title Coming Soon!
11:30 - 12:00
Presentation: Collaborative Edge Computing: A Rising AI Tide Lifts All Boats
- Multi-cloud orchestration friction: Middleware patterns that worked on integrating many admin/control panel functions
- Security policy management: Centralize ways to define your policies and apply the same consistently across all workloads.
- Edge compute management: An approach to installation in heterogeneous infrastrucrure, resource management when capacity is unpredictable.
- Data harmonization across heterogeneous sources: Collaborative model development and inference requires consistent inputs from inconsistent origins. Presenter will discuss the schema management, terminology mapping, and transformation pipeline built to keep downstream models from silently degrading.
Attendees will leave with a practical architectural reference for multi-cloud edge orchestration and a catalog of failure patterns to avoid.
12:00 - 12:20
Networking Break
12:20 - 12:50
Presentation: From AI Factories to the Edge: Architecting Distributed Inference to Unlock Enterprise ROI
AI inference and agents are forcing infrastructure to evolve. As interaction shifts from human to machine-centric, unlocking latency, cost, and performance advantages will be critical. AI Factories excel at foundational model training and large-scale concurrent GPU workloads. However, production inference – especially multi-modal workloads and agentic workflows requiring low-latency responses, multi-step reasoning, and real-time tool calls – demands a different approach. This session demonstrates how distributed inference architectures optimize GPU utilization for responsiveness to maximize ROI by keeping training centralized while deploying fine-tuning, post-training, and production inference on high-performance global networks.
12:50- 13:10
Presentation: The Immutable Edge: Building AI Infrastructure That Scales to 10,000+ Locations
In this session, Saad Malik, CTO of Spectro Cloud, makes the case that immutability is not an optimization for edge AI – it’s a prerequisite. Drawing on real-world deployments across healthcare, retail, and industrial environments, he’ll walk through what a zero-drift, immutable stack looks like in practice: from purpose-built lightweight OS distributions like Hadron through to declarative Kubernetes lifecycle management at 10,000+ locations. You’ll leave with a concrete architectural blueprint and honest lessons from the field.
13:10- 13:20
Presentation: Zero Trust at the Edge
Dr. Chase Cunningham introduces Scylos ZeroCore, a lightweight ephemeral endpoint substrate, and Scylos Switchboard, which enables centralized management and instant endpoint repurposing. Learn how Scylos Inc delivers Zero-Trust as a core function and has modernized enterprise endpoints with its secure, stateless platform architecture and management console which combines to enhance security, deliver containerized applications at scale, reduce operational overhead, and extended hardware lifecycles.
13:20 - 14:10
Lunch Break
14:10 - 14:55
Panel Discussion: Turning Data into Action with AI at the Edge - Key Strategies for Success in Business
Real-time data is only valuable if it leads to meaningful action. Panelists will discuss how AI at the edge accelerates decision making and supports mission-critical operations. Expect insights on governance, deployment models, and cultural shifts required to embed real-time intelligence across the business.
15:00 - 15:20
Presentation: The Safety-Critical Edge: Certifying AI for Passenger Rail Operations
This session focuses on the deployment of Edge AI in safety-critical rail and transit systems, specifically for vehicle positioning, train control, and collision avoidance. When AI directly affects essential functions such as vehicle movement authority or emergency braking, it must meet stringent functional safety requirements. As Edge AI transitions from pilot programs to revenue service, the key challenge is certifying AI/ML systems against safety standards that were originally designed for deterministic logic.
By examining a case study of a driver assistance and collision avoidance system for streetcars, you will gain insights into how to design safe AI systems based on established architectures. You will also learn how to develop the safety cases that regulators can accept for Edge AI applications to be deployed in passenger rail operations.
15:25 - 15:45
Presentation: 20 Years of Interoperability: Why OPC UA is the Foundation for Industrial AI
You can’t run an AI-driven enterprise on fragmented data. While the pressure to modernize and strengthen cyber-resilience is at an all-time high, many organizations remain trapped by inconsistent systems.
This session explores why OPC UA is the strategic choice for standardized, secure interoperability. We will examine:
- The Field Initiative: How the Field Initiative standardizes critical components like drives and instrumentation.
- The Cloud Initiative: How the Cloud Initiative is bridging the gap between assets and digital twins.
- The Outcome: Generating structured, contextualized data directly from the source.
Stop fighting your integration stack. Learn how to leverage interoperable profiles to simplify your architecture and accelerate the journey toward autonomous operations.
15:45 - 16:05
Presentation: AI at the Edge: Transforming Manufacturing Through Real-Time Intelligence
AI is rapidly reshaping manufacturing by bringing real-time intelligence directly to the edge. By collecting and analyzing data where it’s generated, manufacturers can reduce downtime, improve quality, and move toward more autonomous operations. As hybrid AI architectures mature, organizations are finding new ways to balance cloud scale with edge‑level privacy, security, and control. This session explores where the industry is headed and how edge‑driven AI is helping manufacturers optimize infrastructure costs while unlocking the next wave of industrial transformation.
16:05 - 16:25
Networking Break
16:25 - 16:40
Presentation: From Edge Intelligence to Edge Autonomy: Designing Agentic IoT Systems That Think, Plan, and Act
Most IoT systems generate insights—but stop short of action. The next step is edge autonomy, where systems can decide and act in real time.
This session explores how to design agentic IoT architectures that combine sensing, inference, and goal-driven agents to create closed-loop systems that think, plan, and execute. Learn how to move from data to decisions instantly, reducing latency and unlocking real business value at the edge.
