Machine Learning

Computer Vision

Computer vision automates inspection tasks that are too fast, too repetitive, or too precise for human operators. We build vision systems from sensor selection through model training to edge or cloud deployment, designed for the environmental conditions and accuracy requirements of industrial production environments.

99.7%

Defect Detection Accuracy

100x

Faster Than Manual Inspection

Real-Time

Edge Inference

What We Deliver

Computer Vision Services

Practical, production-ready work — not proofs of concept that never make it to real users.

Defect Detection

Quality inspection models that identify surface defects, dimensional anomalies, and assembly errors at production line speed.

Object Detection & Tracking

Multi-object detection and tracking in video streams for inventory counting, people flow, and asset tracking.

Document & Image Analysis

Visual document processing for forms, receipts, ID verification, and handwritten content extraction.

Edge Deployment

Model optimization and deployment to edge devices including cameras, PLCs, and NVIDIA Jetson hardware for low-latency inference.

How We Engage

Common Engagements

01

Production Line QA

Vision system deployed at a manufacturing checkpoint that inspects 100% of units at line speed, replacing manual sampling.

02

Retail Shelf Analytics

Camera-based shelf monitoring that detects out-of-stock conditions and planogram compliance in real time.

03

Medical Image Analysis

Diagnostic support model that assists radiologists by flagging anomalies in X-ray or MRI image series.

04

Construction Site Safety

Video analytics system that monitors PPE compliance and restricted zone violations on active construction sites.

Why InnovTen

What You Can Count On

  • Models trained on your specific product geometry and defect types, not generic datasets
  • Edge deployment for applications where cloud round-trips introduce unacceptable latency
  • Explainability overlays showing exactly what the model detected for operator verification
  • Integration with existing line control systems via OPC-UA, MQTT, or REST APIs
  • Active learning workflows that continuously improve accuracy from operator corrections

Technologies We Use

PyTorch TensorFlow YOLO OpenCV NVIDIA TensorRT ONNX AWS Rekognition Azure Vision

Ready to Get Started?

Tell us about your project and we'll put together a practical path forward.

Talk to Our Team