An Intellyx Brain Candy Brief
BeyondTrucks built a nervous system for trucking logistics which takes in real-time data from private fleets and specialized service providers, employing machine learning and AI to help optimize decisions, manage workflows, and assure detailed delivery execution and payment outcomes to meet company and customer objectives.
In 2019 the US Department of Transportation passed a law requiring that all trucks maintain electronic logbooks and on-the-road telematics devices that relay real-time vehicle and driver data back to the dispatcher. The freight industry’s widespread adoption of this regulatory change opened up a wealth of active logistics data to improve planning and execution.
Unlike a typical on-prem ‘big iron’ transportation management system (TMS) or ERP that batches weekly scheduling and billing plans based on historical orders and invoices, their multitenant TMS gathers highly granular states and activities in a data layer. A variety of algorithmic optimizers then recommend decision alternatives and automatically send routing changes and tasks to drivers in order to improve performance to objectives such as on-time delivery, driver alertness, hazardous material handling, or meeting specific on-site dropoff quantities or setup instructions.
Dispatchers and operators can interface with the system through the SaaS portal, looking at analytics, managing objectives and adjusting workflows in a low-code fashion, or simply by querying the LLM for live information down to any level of detail, for instance, finding an alternate driver if a truck is stuck in the snow, or alerting that a trailer once carried nuts, so that it cannot be used to carry a nut-free food item.
Once outcomes are realized and the rate basis of each activity is known, results and orders are communicated via API to most known ERP, inventory management and supply chain platforms.
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