Sponsored by Infinite Uptime Inc.
Prescriptive AI—the next wave of artificial intelligence that transforms data into prioritized, actionable recommendations—promises to reshape factories by cutting downtime, optimizing workflows, and even redesigning processes on the fly. But is this transformative power accessible to small and mid-sized manufacturers, or will it remain an enterprise-only advantage? With 98% of U.S. manufacturing firms classified as small businesses (SBA, 2025), yet most citing cost and integration hurdles as top barriers to AI adoption, this discussion goes beyond the hype. Panelists will examine practical requirements, affordability, and risk factors, weighing whether Prescriptive AI can be democratized—or if smaller players risk being left behind.
Dr. Raunak Bhinge, a visionary in the field of smart manufacturing and digital technologies, embarked on an innovative journey with Infinite Uptime. With a decade of experience in predictive maintenance and industrial IoT, Dr. Bhinge's goal was clear: to transform the traditional manufacturing industry through cutting-edge technology. His academic background, including a Ph.D. in Mechanical Engineering from the University of California, Berkeley, and a Master’s degree in Automotive Design from IIT Madras, laid a solid foundation for his venture into revolutionizing plant reliability and maintenance.
Sponsored by Cybus
In today’s connected industrial world, data sovereignty is becoming a key differentiator for manufacturers seeking trust, flexibility, and compliance. While the Sovereign Cloud sets the stage for digital independence, the real challenge lies in ensuring sovereignty over industrial data itself.
Join our expert panel as we explore what it truly means not to have data sovereignty — from loss of control and vendor lock-in to limited interoperability — and how these challenges can put innovation and competitiveness at risk.
We’ll discuss how manufacturers can establish true data sovereignty through open technology stacks, interoperable data architectures, and compliance with the European Data Act. Learn how reference architectures in the EU help create trusted, secure, and scalable data ecosystems across the industrial value chain.
AI can’t fix bad data — it amplifies it. On the plant floor, one flawed data stream can cascade into failed AI rollouts, faulty predictions, or million-dollar supply chain disruptions. The real competitive edge isn’t just having AI models — it’s ensuring the data feeding them is accurate, contextual, and trusted.This session brings together leaders tackling the toughest step in industrial AI adoption: how to validate, clean, and structure data before it ever reaches an algorithm. Panelists will dive into:
• Why “data readiness” is now the biggest predictor of AI success.
• How frontline context (not just clean tables) builds trust in outputs.
• Governance frameworks and architectures that make industrial data decision-ready.
If you’re investing in AI for manufacturing, this is the session that shows how to avoid the costliest mistake: feeding your AI the wrong data.
Sponsored by InfluxData
As manufacturers race to implement AI, predictive maintenance, and digital twins, many discover their biggest obstacle isn't algorithms—it's data infrastructure. This panel explores how to build robust time series data architectures that capture, store, and deliver high-velocity industrial data at scale.
Industrial AI is only as good as the context it understands — and most of that context still lives in maintenance logs, PDFs, and legacy documents. This session explores how manufacturers can make that unstructured content usable for AI agents and LLMs without rebuilding existing systems. Experts will share practical steps for transforming document data into verified knowledge that agents can act on, and how to preserve traceability, compliance, and trust along the way.
Sponsored by Arch Systems
By 2030, 2.1 million manufacturing jobs may go unfilled (Deloitte). How can AI copilots, AR/VR training, and digital twins transfer knowledge from retiring experts to a new generation — before the skills gap cripples frontline operations?
Global supply chain disruptions cost companies an average of 45% of one year’s profits over a decade (McKinsey). Can predictive AI, digital twins, and real-time visibility tools finally give manufacturers the resilience they need — before the next crisis hits?
