Most edge AI projects stall between prototype and product—trapped by fragmented tools, hardware constraints, team handoff issues, and a lack of production-ready workflows. This “pilot purgatory” costs teams time, budget, and momentum.

In this webinar, we’ll break down what it really takes to move edge AI from R&D into production—and how teams can design for deployment, scale, and long-term success from day one.

You’ll walk away with practical insights into:

• Why MLOps is the foundation of successful edge AI
  Learn why production-grade edge AI requires more than a great model—and how lifecycle thinking changes outcomes.
• The most common reasons edge AI pilots fail to ship
  Understand where teams get stuck, from data management and tooling gaps to hardware and organizational friction.
• How R&D teams can better align with product and engineering
  Discover strategies for bridging the handoff between ML, embedded, and product teams.
• How advanced edge AI platforms accelerate product velocity
  See how unified workflows reduce complexity, eliminate rework, and shorten time to market.

With an introduction from Harry Mostyn, Director of Sales, Enterprise SaaS Sales at Edge Impulse, and moderated by Zin Thein Kyaw, Director of Customer Solutions Engineering at Edge Impulse, with a panel of practitioners:

• Dr. Natalie Langenfeld-McCoy — Lead Data Scientist, Manager, Nestlé Purina North America
• Dr. Ivan Jursic — Physicist, JUMO
• Dr. Saeid Safavi — CEO, GlobalSense & Co-founder, AutoSonix
• Brandon Shibley — Senior Staff Engineer, Edge Impulse