Despite record global AI spending of $2.5 trillion in 2026, most edge AI projects stall in the pilot phase. Organizations frequently struggle to bridge the gap between training a model in the cloud and operating it reliably at scale in the field, delaying ROI, wasting CapEx, and increasing competitive exposure. The root cause? Edge AI delivery workflows are complicated, resource-intensive, and require months of cross-functional coordination. Underpinning this complexity is friction arising from model governance, dependency packaging, hardware requirements, and a lack of performance testing. Not to mention the historical challenges of edge environments, such as intermittent network connectivity, security risks, and the absence of on-site IT staff. In this webinar, you’ll learn how ZEDEDA Edge Intelligence Platform gets edge AI projects unstuck and orchestrates the complete AI lifecycle in a single control plane, spanning agent behavior, model versioning, inference optimization, performance benchmarking, and distributed infrastructure. This approach eliminates the integration overhead that fragments most enterprise edge AI stacks.