Model Development
- Custom segmentation models for ports and hardware components.
- Transfer learning applied for improved chassis segmentation.
🚀 Project Showcase
End-to-End Powered Computer Vision Deployment for CGS (Canada)
We partnered with CGS to design and deploy a production-grade computer vision system for automated hardware inspection and validation for AR Project. The objective was to replace manual verification workflows with a scalable, high-accuracy AI-driven solution operating under real-world constraints.
Problem Context
CGS needed reliable detection and classification across multiple hardware components, including:
Port availability and segmentation across R2, R4, and R8 cards
Identification of empty vs occupied ports
Detection of capped vs uncapped ports
Classification of jack connections (well-engaged vs improperly engaged)
Structural understanding via chassis segmentation
the solution operates in an air-based (edge) environment with constrained compute and real-time requirements
Solution Architecture
Designed a multi-model computer vision pipeline integrated for AR overlays. Focused on accuracy, robustness, and deployment readiness.
Active Learning Loop
- Continuous loop: inference → error sampling → annotation → retraining.
- Focused on edge cases to improve generalization.
Optimization & Deployment
- YOLO-based architectures for high-precision detection.
- Hyperparameter tuning, dataset balancing, failure-case debugging.
- Delivered models optimized for real-time edge + AR deployment.
Business Impact
~95% accuracy across detection and classification Achieved
Significant reduction in manual inspection effort
Enabled real-time hardware validation
Low-latency, production-ready deployment
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We help teams move from experimental models to production AI systems.
“We have data” → “We have a reliable AI system in production”
By combining
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Deep computer vision expertise
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MLOps and deployment pipelines
Made with TailwinIterative, feedback-driven model improvementd CSS
One platform to turn raw data into production-ready AI: combining data annotation, dataset management, and machine learning workflows in a single system.
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