Amazon SageMaker is a fully managed machine-learning service that enables OEMs like Bigmate to build, train and deploy models quickly and at scale to the Edge. In Bigmate's pipeline, Lambda handles data ingestion, Step Functions orchestrate multiple parallel training jobs (site-specific models, R&D experiments and automated hyper-parameters tuning), while EFS and S3 provide high-throughput storage for annotated optical and LiDAR data.

WARNY is a cutting-edge computer vision system designed to monitor and reduce high-risk interactions between people and machinery in near real-time. Using optical and enhanced sensor technologies such as LiDAR, WARNY delivers precise object detection, dynamic safety zones, and real-time proximity alerts to prevent workplace incidents—particularly in busy warehouse and industrial environments. The latest models are Bigmate-designed neural-network architectures, handcrafted for dense, cluttered scenes and optimised for low-latency edge inference.

The expanded SageMaker workflow allows Bigmate to rapidly train, fine-tune and deploy its custom networks at scale. Customers benefit from faster roll-outs, improved detection accuracy and agile responses to site-specific conditions - all while preserving Bigmate's AI design philosophy: technology that augments human operation and maintaining transparent decision making.

"Our U.S. customers are demanding intelligent, responsive, safe work systems that can adapt to their specific environments," said Mr Gregory Graham, Chief Operating Officer at Bigmate. "Expanding our footprint with AWS SageMaker enables us to deliver exactly that, with the scalability and performance required for North American operations."

Bigmate's WARNY solution is already transforming safe work practices across logistics, manufacturing, and industrial sectors, and this AWS-driven expansion further solidifies its position as a global leader in proactive workplace safe work technology.

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