Trucking AI Company Hemut: The Key to Agentic Action Is Treating Emails, Calls, and Sensors as System Records
Pranav Guda, Head of Product at Hemut, argues that in the trucking industry, system records extend beyond ERP—emails and call logs carry equal or greater operational information. By streaming these three data types via Confluent, the company enables its AI agent, Hemi, to read, correlate, and trigger operating procedures for fault warnings, batch bidding, and automated order entry. The company reports identifying approximately 37,000 hours of manual labor annually in its largest deployment, equivalent to $1.3 million in labor costs.
During an interview with diginomica at Confluent’s Current event, Pranav Guda, Head of Product at Hemut, offered a useful perspective for understanding where agentic AI fits into operations: the trucking industry’s system records have never been limited to ERP alone. He noted that while people typically treat ERP as the system of record, emails and call logs are also systems of record, carrying just as much—if not more—information than the core ERP. Previously, these were true silos because no one could query in real time what was written in an email or what a driver said on a call. Guda believes agentic AI changes this dynamic: when AI can read and classify these unstructured streams in real time, they transform from unqueryable noise into actionable signals.
Hemut’s mechanism involves streaming three types of data—emails, truck sensor feeds, and driver messages—through Confluent Cloud, allowing the company’s AI agent, Hemi, to read and correlate them. Specifically: when a broker asks when a shipment will arrive, Hemi does not ask the dispatcher but instead checks the truck’s actual location; when sensors report a belt failure, the system notifies the fleet before the driver even discovers it. Hemut Founder and CEO Loki Cheema shared an example: a customer told him the system indicated his truck’s belts had torn; he called the driver to confirm, who replied that indeed the belts were torn and the truck would break down within an hour. Cheema said this is what becomes possible after streaming fault data—the signal comes from the sensors, and the action trigger comes from the AI agent reading that stream and notifying relevant parties, rather than relying on someone’s memory or experience.