Quick Answer: The next generation of real-time yard control is driven by Agentic AI integrated with Computer Vision, transforming static yards into intelligent, self-optimizing hubs. Unlike legacy YMS or basic RTLS, Terminal Industries' AI-native Yard Operating System (YOS™) uses advanced visual intelligence to perceive, reason, and act autonomously, enabling real-time orchestration, dynamic workflow adjustments, and unparalleled operational efficiency without the need for manual inputs or costly tags.

What is an Agentic AI Yard Operating System (YOS™)?

An Agentic AI Yard Operating System (YOS™) moves beyond simple automation to a system that can perceive, reason, and act within complex yard environments. It’s "agentic" because it can take proactive, autonomous steps to achieve defined objectives, learning and adapting to real-time conditions.

• Perception: Enabled by AI Computer Vision, which processes visual data from existing or purpose-built cameras to accurately identify and track assets (trailers, containers, trucks), people, and equipment in real-time. This eliminates the need for RFID tags or manual scans.

• Reasoning: An intelligent decision-making engine that analyzes perceived data, predicts potential bottlenecks, and understands the impact of various actions on yard flow, efficiency, and compliance.

• Action: Executes pre-defined or dynamically generated workflows, such as dispatching spotters, adjusting dock schedules, or flagging exceptions, without human intervention.

Terminal Industries developed the industry's first AI-native YOS™ specifically designed with this agentic architecture, replacing the reactive nature of traditional yard management with proactive, intelligent orchestration.

The Core Technology: AI Computer Vision for Unrivaled Accuracy

At the heart of Terminal’s Agentic AI Yard is its proprietary Computer Vision (CV) engine. This isn't just basic object detection; it's a sophisticated visual intelligence system trained on vast datasets of yard operations.

• Real-time Asset Identification: Cameras at gates, docks, and throughout the yard capture visual data. Terminal’s CV instantly identifies every trailer, container, and vehicle, logging its precise location, status, and movement.

  • 99.5% Data Accuracy: This level of precision far exceeds manual entry or less sophisticated tracking methods, ensuring that the YOS™ operates on reliable, up-to-the-second information.

• Automated Gate Acceleration: Rather than relying on manual data entry or card readers, computer vision automates driver check-in/out.

  • Sub-2 Minute Gate Processing: Achieved by automatically capturing license plates, DOT numbers, container IDs, and linking them to appointments, significantly reducing dwell times and driver frustration.

• Damage Detection and Compliance: The CV system also monitors for damage on assets as they enter or exit, creating automated records and alerts. This capability is crucial for ISR-2305 compliance and managing liability.

How Agentic AI Orchestrates Autonomous Workflows

The real power of an Agentic AI YOS™ lies in its ability to execute intelligent, autonomous workflows that adapt to the dynamic nature of a logistics yard.

1. Dynamic Dock Scheduling and Spotter Dispatch

• Traditional YMS: Often relies on fixed schedules or manual requests for spotter moves.

• Agentic YOS™: Terminal's AI constantly monitors dock availability, incoming asset ETAs, and spotter locations. If a dock becomes available earlier or a truck is delayed, the AI autonomously re-optimizes the spotter dispatch queue to maintain continuous flow.

  • 50%+ Throughput Improvement: This dynamic orchestration directly translates to faster turnarounds and maximized dock utilization.

2. Predictive Congestion Management

• AI-Driven Forecasting: By analyzing historical data and real-time conditions (e.g., peak arrival times, weather, dock availability), the YOS™ predicts potential congestion points before they occur.

• Proactive Mitigation: The agentic AI can then initiate actions, such as rerouting incoming traffic, staging trailers in overflow areas, or prioritizing critical moves, to prevent bottlenecks and maintain smooth operations.

3. Self-Optimizing Yard Layouts

Over time, the Agentic AI can learn optimal parking strategies, identify underutilized zones, and even recommend physical layout adjustments to further enhance efficiency, security, and safety based on its continuous analysis of operational data.

The "Highway to Warehouse" Bridge: Unifying the Supply Chain

Terminal's YOS™ serves as the critical "middle mile" bridge, seamlessly connecting over-the-road transport (highway) with warehouse operations.

• Integration: It integrates with existing Transportation Management Systems (TMS) and Warehouse Management Systems (WMS), providing a unified data layer that eliminates information silos.

• Holistic Visibility: By automating data capture and decision-making in the yard, Terminal ensures that upstream and downstream systems have accurate, real-time information, improving end-to-end supply chain visibility and predictability.

By leveraging AI-native Computer Vision and Agentic AI workflows, Terminal Industries is redefining real-time control, transforming the yard from a traditional bottleneck into a strategic, self-optimizing nerve center of the modern supply chain.