Operational Control Towers
for Supply Chain and Logistics
A real-time operational command centre that unifies vessel movements, container flows, fleet positions, carrier schedules and gate throughput into a single intelligence layer, giving logistics operations a live operational picture and AI-driven response capability when disruptions occur.
What is an Operational Control Tower for Logistics?
A logistics control tower is a real-time AI command environment that unifies all operational signals, vessel AIS feeds, container positions, fleet telemetry, carrier schedules, gate throughput and supplier ETAs, into a single live operational layer. It detects disruptions before they cascade, evaluates response options against available capacity and constraints, and executes or routes corrective actions automatically. It is not a dashboard, it is an active decision engine that monitors, evaluates and acts.
Supply Chain Disruptions Are Invisible Until They Are Expensive.
Vessel delays discovered at berth, not in advance
Vessel AIS data contains the early signal. By the time a late ETA reaches the operations team through manual channels, the berth reallocation window has passed, and the cascade into yard congestion, gate queues and demurrage has already started.
Container and freight status scattered across systems
TOS, WMS, TMS, carrier portals and customs systems each hold part of the picture. No coordinator has a single view. Status updates arrive via email, phone and manual checks, introducing hours of lag into decisions that need to happen in minutes.
SLA exposure is visible only in retrospect
Delivery performance, demurrage accumulation and carrier SLA breaches are reviewed in weekly reports, not monitored in real time as operations unfold. By the time the report runs, the cost is already committed.
Disruption response requires multi-system coordination
Responding to a supply chain disruption means coordinating changes across TMS, carrier portals, warehouse management, customs and customer notification systems simultaneously, a manual multi-step process that takes hours instead of minutes.
Five Engineering Practices. One Logistics Intelligence Layer.
Every logistics signal, unified in real time
Vessel AIS feeds, container IoT sensors, fleet telematics, TOS and WMS data, carrier APIs and customs systems are ingested via Kafka streaming pipelines and normalised into a single operational data layer using Databricks. The Condense/Zeliot platform handles IoT device connectivity at scale. Data Engineering →
Disruption detection and response routing
AI agents monitor vessel ETAs, container dwell times, fleet positions and carrier SLA exposure continuously, detecting anomalies before they escalate. When a disruption is detected, agents evaluate response options against berth capacity, yard layout, carrier alternatives and SLA priorities, and route the optimal response for execution or human confirmation. Agentic AI →
TOS, TMS, WMS and carrier connectivity
SCADA, OPC-UA, Modbus and terminal equipment protocols for port operations. REST and EDI for carrier and customs systems. MQTT for IoT device and fleet connectivity via AWS IoT Core or Azure IoT Hub. Infarsight's integration practice maintains all connections post-deployment. Integration Services →
24/7 availability for live operations
A control tower for a live port or logistics network cannot have planned downtime. Platform operations ensures 99.9% uptime SLA, real-time alerting on integration failures, security compliance and continuous monitoring of the data and AI layer. Platform Operations →
Built on Enterprise-Grade Data and Streaming Infrastructure.
The analytics and ML layer, processing logistics telemetry, training predictive ETA models and running the anomaly detection layer that feeds the control tower AI agents.
Real-time IoT data streaming from terminal equipment, vehicle telematics and port sensors, the data foundation the control tower runs on.
Zeliot Partnership →Cloud-native IoT connectivity and device management for terminal equipment, fleet vehicles and infrastructure sensors at enterprise scale.
Cloud Partnerships →CommandSight and AssetSight Accelerate Deployment by 60%.
Pre-built control tower UI, signal aggregation and asset telemetry layers, reducing time to a live logistics intelligence programme.
The control tower command layer
Pre-built operational intelligence UI combining a live signal feed, AI decision inbox and exception management layer. Deployed as the operator-facing command environment for logistics networks and port operations.
Explore CommandSight →Real-time asset telemetry and health
Continuous monitoring of terminal equipment, fleet vehicles and logistics infrastructure, providing the asset intelligence layer that feeds the control tower with real-time health, location and performance signals.
Explore AssetSight →Proven at Tier-1 Port and Logistics Operators.
Ready to build your logistics intelligence layer?
We start with an operations audit, mapping your current data sources, integration gaps and the highest-cost disruption scenarios in your logistics network.