AI in Supply Chain and Logistics

We build AI forecasting systems that help logistics teams predict demand, inventory needs, shipment volumes, and capacity requirements more accurately. What we do:

• Forecast order, shipment, and inventory demand using historical and real-time data
• Combine ERP, WMS, TMS, sales, seasonality, weather, and market signals
• Generate forecasts by SKU, warehouse, region, customer, or transport lane
• Detect demand anomalies and sudden changes automatically
• Support replenishment, capacity planning, and procurement decisions
• Continuously retrain models as new operational data becomes available

What you get: More accurate planning, fewer stockouts and excess inventory, and better alignment between warehouse capacity, transportation resources, and expected demand.

We use AI and automation to improve how goods move through warehouses, from receiving and putaway to picking, packing, and dispatch. What we do:

• Optimize slotting based on order frequency, product attributes, and movement patterns
• Build intelligent task allocation for warehouse workers and robotic systems
• Integrate WMS platforms with AMRs, conveyors, scanners, sensors, and other automation equipment
• Apply computer vision for inventory checks, damage detection, and operational monitoring
• Optimize picking routes and order batching
• Analyze warehouse activity to identify congestion, bottlenecks, and underused capacity

What you get: Faster fulfillment, less manual travel and handling, improved inventory accuracy, and higher warehouse throughput without relying solely on additional labor.

We develop AI-powered routing systems that continuously find more efficient ways to move vehicles, shipments, and drivers. What we do:

• Optimize routes using delivery windows, capacity, driver hours, vehicle type, traffic, and service constraints
• Recalculate routes when orders, traffic, weather, or delivery conditions change
• Use historical delivery data to improve ETA and travel-time predictions
• Support multi-stop, multi-depot, and last-mile routing scenarios
• Balance cost, service level, distance, and fleet utilization
• Integrate optimization engines with TMS, dispatch, telematics, and driver applications

What you get: Lower mileage and transportation costs, more reliable ETAs, better fleet utilization, and faster response to disruptions during the delivery day.

We use equipment and vehicle data to identify early signs of failure and help maintenance teams act before breakdowns interrupt operations. What we do:

• Collect telemetry from vehicles, warehouse equipment, sensors, and IoT devices
• Monitor vibration, temperature, engine data, battery health, usage, and other condition signals
• Detect patterns that indicate abnormal equipment behavior
• Estimate failure risk and remaining useful life where sufficient data is available
• Prioritize maintenance based on operational impact and asset condition
• Connect alerts with fleet management, maintenance, and work-order systems

What you get: Fewer unplanned breakdowns, better maintenance scheduling, longer asset life, and reduced disruption to fleet and warehouse operations.

We build logistics visibility systems that combine location, status, and operational data into a current view of shipments, vehicles, and assets. What we do:

• Collect GPS, telematics, mobile, IoT, carrier, and partner data
• Normalize events from multiple transportation systems into one tracking layer
• Generate dynamic ETAs based on current movement and historical performance
• Detect delays, route deviations, missed milestones, and stalled shipments
• Trigger automated alerts and customer notifications
• Provide dashboards, maps, APIs, and portals for internal teams and customers

What you get: Better shipment visibility, earlier detection of exceptions, more accurate customer updates, and less manual status checking across carriers and systems.

We develop AI systems that detect suspicious activity and operational risks across logistics transactions, shipments, carriers, and business processes. What we do:

• Analyze shipment, payment, carrier, user, and transaction patterns for anomalies
• Detect unusual route changes, duplicate activity, suspicious claims, or abnormal account behavior
• Score transactions and events by risk level
• Combine machine learning with business rules and known fraud indicators
• Route high-risk cases to human reviewers instead of automatically blocking legitimate activity
• Maintain audit trails explaining which signals contributed to an alert

What you get: Earlier detection of suspicious activity, fewer manual reviews, stronger control over operational and financial risk, and more consistent investigation workflows.

We build data and AI capabilities that help logistics companies measure emissions and identify ways to reduce the environmental impact of transportation and warehouse operations. What we do:

• Calculate emissions using shipment, route, vehicle, fuel, distance, and load data
• Structure reporting around frameworks such as the GHG Protocol and ISO 14083 where applicable
• Compare emissions by route, carrier, transport mode, customer, or shipment
• Model lower-emission routing and consolidation scenarios
• Identify empty miles, underutilized capacity, and inefficient movements
• Integrate sustainability metrics into TMS, analytics platforms, and customer reporting

What you get: More reliable carbon reporting, visibility into major emissions sources, and practical data for reducing empty miles, improving load factors, and evaluating lower-carbon transportation options.