OCR, Object Detection & Video Analytics
Computer Vision
Turn your cameras and document images into intelligence. We build computer vision systems for quality inspection, document processing, safety monitoring, and real-time video analytics that operate at production scale.
Challenges We Solve
Sound Familiar?
- Manual visual quality inspection that's slow, inconsistent, and expensive
- Unstructured document images blocking downstream automation
- Safety and compliance monitoring that relies entirely on human review
- No visibility into what's happening on your production floor or premises in real time
- Document OCR solutions with poor accuracy on domain-specific formats
Our Approach
How We Help
Quality Inspection Systems
Real-time defect detection on production lines using object detection and anomaly detection models, with configurable defect classification thresholds.
Intelligent Document Processing
OCR + layout analysis + NLP extraction pipelines for contracts, invoices, forms, and reports — with structured output and confidence scores.
Video Analytics
Object tracking, people counting, safety event detection, and behavioral analysis on live or recorded video feeds.
Custom Object Detection
Fine-tuned YOLO or DETR models for domain-specific object recognition — medical images, satellite imagery, industrial components, or retail shelves.
Tech Stack
Technologies We Use
How We Work
Delivery Process
Visual Data Assessment
Review image/video quality, resolution, lighting conditions, and existing labels to determine model feasibility.
Labeling & Data Pipeline
Set up annotation tooling, labeling guidelines, and QA workflows. We can assist with annotation or integrate your labeling team.
Model Selection & Baseline
Benchmark pre-trained Azure AI Vision and YOLO models before custom training to establish the performance gap.
Custom Training
Train domain-specific models on your labeled dataset with data augmentation, class balancing, and transfer learning.
Edge / Cloud Deployment
Deploy to Azure IoT Edge for on-premise inference or Azure Container Apps for cloud-based processing, with ONNX optimization.
Integration & Alerting
Integrate with your existing systems — PLC, SCADA, ERP, or alerting platforms — and set up dashboards for operators.
What You Get
Deliverables
Every engagement has a defined scope and concrete outputs. No vague “consulting reports” — you get production-ready artifacts.
- Trained computer vision model (ONNX-optimized)
- Inference service (edge or cloud deployed)
- Labeling pipeline and annotation guide
- Integration connectors to downstream systems
- Operator dashboard with detection visualization
- Model performance report with precision, recall, and mAP metrics
Why StarkLogik
What Makes Us Different
Edge-to-Cloud Architecture
We design for real-time constraints — deploying inference at the edge when latency requirements demand it, with cloud aggregation for analytics.
Domain-Specific Training
Generic vision APIs fail on specialized domains. We fine-tune on your specific defect types, document layouts, or object classes for production-grade accuracy.
Operator-First UX
Every vision system we deploy includes an operator interface that makes model outputs actionable — detection overlays, confidence displays, and alert workflows.
FAQs
Common Questions
Get Started
Ready to Get Started with Computer Vision?
Book a free 30-minute call with our engineering team to discuss your use case.