Optimize your route and capacity

Predict customer demand and the duration of shipping journeys, while providing customers with real-time transparency to the state and location of their cargo.

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Customer satisfaction
Provide customer with peace of mind through increased transparency and control over their cargo.
Effective fleet capacity
Accurately predict demand, reduce idle capacity and increase your available fleet capacity.
Order fulfillment
Identify bottlenecks, shortages and surpluses across your network and redistribute your fleet.
Customers are demanding greater transparency
The logistics industry has vast, complex distribution networks that are highly integral to their customers’ business. These networks are expected to run seamlessly; securely distribute large quantities of goods quickly; and adapt to customers’ changing demands, often at short notice.

Meanwhile, a huge amount of data is being produced - from vessel geolocation data to humidity sensors within containers to customer bookings. Much of the data is highly complex; the source and systems may vary; and the format of the data can be vastly different. This makes data harmonisation difficult and puts many challenges in the way of this data being used to power decisions and processes.

However, these challenges are worth facing. Addressing the opportunities provided by digitalization, specifically by big data, will lead to significant benefits for logistics companies. As a first step, harmonization of this data can be used to provide unprecedented transparency both internally and with customers and partners. Secondly, customers can turn the vast and disparate data landscape into a powerful predictor of decision-influencing factors. In short, data science, machine learning and artificial intelligence can be applied to turn the unpredictability into routine; to turn chaos into order.
Our logistics use cases
We have a number of use cases that enable logistics companies to provide greater transparency to their customers, while more efficiently moving cargo from A to B.

Empty Container Optimization

Combine demand, route and journey time predictions to optimize the movement of containers. Further, with shipment data and container capacity, ensure that capacity is fulfilled. Automate the process of container disposition or provide a powerful predictive tool to disposition teams.

Customer & Partner Apps

Leverage increasing IoT touchpoints, such as geolocation data and humidity or CO2/O2 sensors within containers, to provide customers and partners with unprecedented access and control to the whereabouts and state of their cargo. Use advanced analytics to detect early warning signals and prevent the degradation of cargo.

Predictive Fleet Maintenance

Optimize your fleet maintenance schedules by identify drivers of fleet breakdown. Use  vehicle sensor data, vehicle usage data and historical maintenance schedules to predict drivers of vehicle breakdown. Use these predictions to identify when vehicles should be maintained, reducing unnecessary maintenance and increasing your active fleet.

Contiamo selected by Deutsche Bahn Mindbox

DB Mindbox selected Contiamo to join their accelerator program, where Contiamo worked directly with their transport vessel disposition team at DB Cargo to predict the duration of cargo journeys.

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