According to analyst firm Gartner, 75 percent of enterprise-generated data will be created and processed at the edge by 2025; allowing agencies to make real-time, accurate decisions where it matters the most. The challenge is that while inferencing at the edge is becoming more common, large-scale AI and machine learning workloads still aren’t typically completed at the edge. They’re sent back to a core data center for processing, adding significant time to create and deliver results. Join this session to learn how KubeFrame, an open-source solution that combines portable hardware, powerful open-source software, and industry-leading security makes real-time AI-driven edge processing a reality. We’ll share technical details and explore use case examples from military operations, smart cities, crisis response, and healthcare centers.