Nicolás Carlo
I build telematics and machine safety systems for heavy machinery. Nine years in telematics, seven of those on plant and two in oil and gas, and the last five putting computer vision on top of it.
I architected and built an AI proximity intelligence platform for one of the UK's largest plant hire fleets, reading camera feeds with human form recognition to detect people entering a machine's danger zone, and filtering out the false alerts that render conventional systems unusable. I designed the detection pipeline, the alert logic, and the integration into the telematics platform underneath it. In 2026 it won Best Safety Initiative at the European Rental Awards, chosen from more than seventy entries by an international panel. It runs across sites operated by major UK housebuilders.
I have since rebuilt a fleet telematics platform from the ground up, designing the domain model, the contract first API and the data architecture.
Underneath the AI is fifteen years architecting enterprise software in C# and .NET across construction, finance and government, including digital government platforms across Latin America, and a First Class degree in Computer Science with an AI focus from the University of London.
That combination is the reason Talvo exists in this form. The problems described on this site are not visible from outside the industry, and the architecture that answers them is not obvious to anyone who has not built both the detection stack and the platform underneath it. I have spent the last several years doing both, on real fleets, for a company that hires machines out every day. Talvo came out of the frustration of watching good technology fail for reasons that had nothing to do with the technology. The patent was filed in February 2026. What I am building does not just record what happens on a site, it reasons about it as it happens.