Where Should Your Model Live? A Framework for Tiering Computer Vision Deployments| Voxel51

Where should a computer vision model actually run - on-device, near the edge, or in the cloud? It's a decision that looks simple until requirements like latency, cost, connectivity, and update cadence start pulling in different directions, often revealing themselves only after deployment. Drawing on hands-on experience developing and deploying CV models across Hailo, Nvidia, Qualcomm and AWS platforms, this talk introduces a practical framework for tiering computer vision deployments based on real project requirements and constraints. Discussion will include what changes at each tier - from development to deployment to monitoring and update strategy - with relevant industry examples. Attendees will leave with a set of questions or a framework they can use to place their own CV projects into the right tier. Ajaykumaar Sivacoumare is an AI Software Engineer specializing in computer vision and edge AI, with production experience developing and deploying CV models across Nvidia, Hailo, Qualcomm and AWS-based platforms. His work also spans CV-based gait analysis and feature tracking for bipedal robots using pose estimation and multi-view geometry at NYU's Applied Dynamics Optimization Lab, where he holds an MS in Robotics.