See smarter. Detect faster. Decide with confidence.
MLVision unifies object detection, classification, and video analytics into one production dashboard — so your teams ship vision models with measurable accuracy and sub-frame latency.
Four pillars of production vision AI
Modular pipelines from camera ingest to governed deployment — built for factories, retail, and public safety workloads.
Real-Time Object Detection
YOLO-class and transformer detectors with NMS tuning, class balancing, and edge-optimised ONNX export for sub-20ms inference.
Semantic Segmentation
Pixel-level masks for defect inspection, occupancy mapping, and autonomous navigation with IoU-tracked quality gates.
Video Stream Analytics
Multi-camera RTSP ingest, temporal tracking, and event triggers with frame-accurate audit logs for compliance teams.
Edge Vision Deployment
Jetson and Intel OpenVINO bundles with OTA updates, drift alerts, and offline-first inference for remote sites.
CV · ML · Ops — one governed pipeline
From labelled datasets to monitored production endpoints without handoffs between siloed teams.
End-to-end vision engineering
Consulting, implementation, and managed operations for Canadian and North American enterprises.
Object Detection
Custom detectors, transfer learning, and production APIs with SLA-backed uptime.
Image Classification
Multi-label and hierarchical classifiers with calibration and confusion-matrix reporting.
Video Analytics
Tracking, counting, and anomaly detection across distributed camera networks.
CV Fine-Tuning
Domain adaptation on your imagery with reproducible training manifests.
MLOps for Vision
CI/CD for models, canary releases, and observability dashboards your ops team trusts.
Deploy on proven inference stacks
Certified integrations across GPU clouds, edge devices, and vision-optimised runtimes.
- NVIDIA DGX & Jetson Orin (TensorRT)
- AWS EC2 G5 / Inferentia & SageMaker
- Google Cloud TPU & Vertex AI Vision
- Microsoft Azure ML & NC-series VMs
- Intel OpenVINO & Movidius VPU
- ONNX Runtime & Triton Inference Server
- Kubernetes + NVIDIA GPU Operator
- Roboflow & CVAT annotation sync
Trusted where precision matters
“MLVision cut our line-defect false positives by 41% in six weeks. The dashboard gives QA leads frame-level evidence — no more debating model guesses.”
“We process 1,200 camera feeds nightly. Their video analytics module flagged occupancy anomalies our legacy rules missed entirely.”
“Fine-tuning on our aerial imagery shipped with documented mAP gains. Legal and ops reviewed the same metrics — that clarity closed the project fast.”
Ready to see what your cameras miss?
Schedule a vision audit. We map your feeds, baseline accuracy, and deliver a deployment plan you can defend to leadership.
Start Your Vision Audit