Move AI models from prototype notebooks into field-ready systems.
Computer vision and inference systems for real devices, cameras, and constrained compute.
Model deployment
Optimization, conversion, and runtime integration for target hardware.
Vision pipelines
Camera input, preprocessing, detection, classification, and event logic.
Production monitoring
Telemetry, confidence metrics, logs, and retraining feedback loops.
Cancer Detection in Pets
ML-based early detection of cancer cells in pets using CNN and OpenCV
Python / CNN / OpenCVLithium Battery Fire Prevention
An intelligent fire prevention system for lithium batteries — relevant for electric vehicles, buses, and energy storage systems. Combines advanced sensors, AI anomaly detection algorithms, and an early warning system based on machine learning to identify failure patterns before they become disasters.
Deploy AI at the edge
Turn models, cameras, and device constraints into a working product flow.
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