YardFlow scales automation across 200-plus sites

YardFlow is expanding its yard-automation technology from 26 facilities to more than 200 sites for a major beverage shipper, taking a system initially used to standardise driver check-in and documentation across a much larger distribution network.

The first 26 sites have processed close to two million shipments, according to YardFlow, with the platform running at a reported 99.9% uptime. Company analysis of the deployment found that the customer moved almost 5% more freight without increasing headcount. Those figures relate to this specific network and should not be read as guaranteed results for other operators.

The expansion moves the platform beyond a limited pilot or a handful of flagship distribution centres. The customer is extending the operating model into more than 200 locations, including smaller sites, with the aim of standardising processes that can otherwise vary substantially from one warehouse to another.

YardFlow began with the driver’s journey through the facility: arrival, check-in, dock allocation, signed transport documentation, and departure. Drivers do not need to install an application, and QR-code check-in can be used where appropriate. Digitising those steps reduces dependence on gatehouse paperwork and creates a timestamped record of movements through the site.

Documentation is a significant part of that process. Bills of lading, proof of collection, signed paperwork, and appointment information often pass through separate systems or remain partly paper-based. When a dispute later arises over timing, quantities, or collection, warehouse teams can spend time reconstructing events from records that were never designed as one continuous workflow.

YardFlow has added yard-management functions covering trailer inventory, spotter movements, and dock coordination. It is also introducing machine vision using cameras at gates and on yard vehicles. Those cameras can validate truck and trailer movements and provide another source of information against which instructed moves can be checked.

The wider rollout turns yard digitalisation into a network-standardisation project. Large warehouse estates often accumulate local procedures around particular labour teams, building layouts, customers, and transport patterns. That local knowledge keeps facilities moving, but it can make central comparison difficult because two sites may record the same event in different ways.

Standardising arrival, movement, and departure events creates a more consistent dataset. Once check-in time, dock assignment, trailer position, loading completion, document signature, and departure are captured through the same process, dwell and throughput can be compared on a more credible basis across the estate.

That consistency is useful even before physical automation is introduced. Despatch teams can identify recurring queues, long trailer dwell, underused doors, or differences between sites that would otherwise be masked by incompatible local records. Operational improvement then starts from measured events rather than anecdote.

The machine-vision layer adds another control point. YardFlow says cameras can identify arriving equipment, monitor movement through the site, and cross-check carrier identity against US Department of Transportation and motor-carrier records. The function has a security role as cargo theft and fraudulent carrier identity place more pressure on gate controls, although software still has to sit alongside physical security and exception procedures.

Scaling from 26 to more than 200 facilities will test whether the model can retain consistency across sites with different staffing, connectivity, yard geometry, carrier behaviour, and shipment volumes. A process that performs well at a high-volume distribution centre may encounter different constraints at a smaller location, where gatehouse staffing or wireless coverage is more limited.

The rollout also has to avoid replacing local inconsistency with rigid central rules that do not fit every site. Standard events and data definitions can be common across the network while physical workflows still allow for differences in door layout, traffic direction, trailer storage, and local safety requirements.

Yard digitalisation sits alongside growing work on automating physical trailer movements. ISEE’s work on autonomous yard trucks represents the next layer, where software begins directing vehicles without a driver. That technology depends on reliable trailer-location data, clear task instructions, and disciplined site processes.

YardFlow’s sequence starts further upstream. Driver workflows and documentation are standardised first, yard-management functions are added, machine vision improves verification, and physical automation can then operate on top of a more structured information layer.

The reported 5% throughput gain will attract attention, but the wider deployment provides a more demanding test. More than 200 facilities create far more exceptions, user groups, hardware environments, and local operating practices than 26. Maintaining a common process at that scale is likely to matter more than reproducing one headline percentage at every location.

If the rollout succeeds, the customer will gain a network-level view of yard activity rather than another collection of isolated systems. That can support staffing, carrier management, door utilisation, security, and later automation decisions with a common operating record across the estate.

The next evidence will come from how the platform performs after the expansion reaches smaller and more varied sites. Uptime, adoption, dwell reduction, throughput, exception rates, and the amount of manual intervention still required will show whether the initial deployment has produced a scalable operating model rather than a successful first cluster.