Deploy Vision Models with Zero DevOps Overhead
From inference optimization to auto-scaling and real-time monitoring—Matrice simplifies model deployment across cloud, edge, and on-prem environments.
Deploy Any Vision Model in a Single Click
Classification, detection, and segmentation models without managing infrastructure. One-click deployment from training pipeline. Supports Vision Transformers and CNN models. Automatic inference optimization for runtime speed. Minimal configuration required for deployment. Integrates with edge, cloud, or hybrid systems.
Auto-Scaling Based on Real-Time Traffic
Maintain low latency and cost efficiency with automatic GPU resource scaling. Scales GPU instances up during high traffic. Shuts down idle resources to reduce cost. Supports NVIDIA GPU acceleration across clouds. Optimized for AWS, GCP, and OCI environments. No manual tuning or infrastructure setup required.
Visualize Real-Time Inference Traffic
Track model performance, monitor load, and detect drift from a unified dashboard. Real-time traffic and latency metrics. Visual drift detection and anomaly tracking. Customizable inference thresholds. Traffic visualization by endpoint and model. Identify bottlenecks before they impact UX.
Detect & Visualize Model Drift
Spot data distribution changes with visual tools and trigger retraining workflows automatically. Visual drift plots for input distributions. Annotate drift samples for active learning. Integrates with ML-assisted labeling tools. Create datasets directly from drift samples. Supports drift monitoring for critical tasks.
Transforming Pixels
into Intelligence
Real time intelligence for existing cameras; One platform. Many Applications. Any Scale