Mayank Sehgal
Senior Product Manager
Port Global Ltd
Mayank Sehgal is a Senior Product Manager at Port Global Ltd in London, where he works on connected fleet and platform products. Over eight years he has built AI systems that operate in the physical world - autonomous agricultural machinery, warehouse robotics, industrial computer vision and connected urban fleets. His work sits consistently at the point where a technically capable system meets the people expected to rely on it.
Currently at Port, he owns the core platform that the connected urban fleet runs. At Monarch Tractor, manufacturer of the first fully electric driver-optional tractor, he led digital product for the autonomy platform. The platform worked; the harder problem was that growers who owned autonomy-capable machines were not operating them autonomously. Resolving that meant rebuilding the product around standards defined by the people doing the work rather than around internal efficiency targets, and removing friction from the phases before anyone touched the technology. The setup, configuration and commissioning that determine whether a capability is ever genuinely used.
Earlier in his career he trained and deployed computer vision systems for industrial safety across factory and mining sites, where detecting unsafe behaviour proved considerably easier than changing it, and delivered collision-avoidance and real-time location systems for warehouse material-handling fleets. A recurring theme across all of it: automated systems earn trust through how legibly and safely they fail, not through how capable they are at their best.
He holds an MS in Management Science and Engineering from Columbia University and began his career in data science and software engineering. He writes and speaks on connected hardware product management, applied AI in production systems, and designing human oversight into automated decisions.
Currently at Port, he owns the core platform that the connected urban fleet runs. At Monarch Tractor, manufacturer of the first fully electric driver-optional tractor, he led digital product for the autonomy platform. The platform worked; the harder problem was that growers who owned autonomy-capable machines were not operating them autonomously. Resolving that meant rebuilding the product around standards defined by the people doing the work rather than around internal efficiency targets, and removing friction from the phases before anyone touched the technology. The setup, configuration and commissioning that determine whether a capability is ever genuinely used.
Earlier in his career he trained and deployed computer vision systems for industrial safety across factory and mining sites, where detecting unsafe behaviour proved considerably easier than changing it, and delivered collision-avoidance and real-time location systems for warehouse material-handling fleets. A recurring theme across all of it: automated systems earn trust through how legibly and safely they fail, not through how capable they are at their best.
He holds an MS in Management Science and Engineering from Columbia University and began his career in data science and software engineering. He writes and speaks on connected hardware product management, applied AI in production systems, and designing human oversight into automated decisions.
mayank.sehgal@port.app