Why Most Video AI Deployments Break at Scale: The Missing Role of Ingestion Layers (S06 Explained)
Video AI is promising something strong, to transform inactive camera shots into real-time decisions. And in the small scale, that promise most is true. Even a pilot using a few cameras, consistent connectivity, and a controlled setting can achieve impressive outcomes accurate detections, valuable alerts and clear ROI. However, something […]
Why ‘Send Everything to Cloud’ Fails in Video Analytics — A Bandwidth and Latency Breakdown
Introduction: The Most Expensive Mistake in Video AI When teams start building video analytics systems, the default instinct is simple: “Let’s send all video feeds to the cloud and process everything there.” It feels logical. Cloud is scalable.Cloud has GPUs.Cloud simplifies architecture. But here’s the reality most teams face within […]
Why Storing More Video Doesn’t Improve Insights: Rethinking Data Retention in AI Systems
At some point in almost every deployment, this conversation happens. Someone asks:“Should we increase retention to 60 days?” Someone else adds:“Storage is cheap anyway… let’s just keep everything.” Nobody really pushes back. Because it feels like a safe decision. And honestly, early on, it is. But give it a few […]