Computer Vision Platform — Multi-Model CV System With Monitoring

I will build a production computer vision platform — supporting multiple CV models for different visual tasks, a unified image ingestion pipeline, model inference API with GPU acceleration, model performance monitoring, and a management interface enabling your team to deploy updated models without downtime. Computer vision platforms serving multiple use cases (product classification, defect detection, and label OCR simultaneously) need shared infrastructure for image ingestion, GPU resource management, and model serving — building each CV application independently duplicates infrastructure and creates operational fragmentation that a unified platform eliminates.

The platform covers an image ingestion API, GPU-accelerated inference server (Triton or TorchServe), multiple model serving with version management, performance monitoring with per-model accuracy tracking, a model deployment pipeline, and a management dashboard for operational visibility.