How Presien Uses Claude to Reduce Construction Safety Events by 70%
Presien is an Australian physical AI company that runs computer vision models directly on heavy construction and mining machinery to detect hazards in real time. By connecting its six-year proprietary data infrastructure to Claude through MCP servers, Presien built /loop — an agentic intelligence platform that monitors worksites around the clock and surfaces risks before they become incidents. Within three months of early deployments, critical safety events dropped by more than 70% and safety managers replaced hours of daily video review with AI-generated morning briefings.
Tools & Technologies
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Challenge
Construction and mining sites generate massive volumes of safety data — video feeds, sensor events, detection logs — but less than 5% is ever acted upon, leaving safety managers buried in manual review with no scalable way to reason across incidents, site conditions, and regulations simultaneously.
Solution
Presien connected its computer vision data infrastructure to Claude through MCP servers, building /loop — an agentic platform that monitors thousands of machines 24/7, cross-references detections against safety policies and regulations, and surfaces prioritized risks and pre-drafted actions to managers each morning.
Full Story
Presien spent six years building computer vision models that run directly on heavy machinery — excavators, mining trucks, bulldozers — detecting hazards like workers in blind spots, excavators operating near site boundaries, and vehicles moving without spotters. By the time the company was ready to build an intelligence layer on top of this data, it had something rare: a continuous, real-world stream of physical safety events from active worksites across the globe.
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