The provider of real-time transparency in transport has announced at its conference Visibility Now! the introduction of a new layer of functionality within its platform. According to the company, Shippeo AI will analyze transport data in real time and thus accelerate operational decisions in supply chains.
Intelligent real-time data analysis
According to the company, Shippeo AI is fully integrated into the existing platform. The solution uses SLA-based transport data, which, according to Shippeo, are among the industry's most precise. The aim is to derive concrete actionable recommendations for logistics processes from this information.
Shippeo AI can be used via two main interfaces. The Sidekick function supports users in day-to-day operations, for example in the analysis of missing arrival times. The Workspace mode enables in-depth analyses, for example to compare the data quality of different freight forwarders.
The core of the new layer is the so-called Agent Library. This is a collection of specialized AI agents that access Shippeo
data to take on tasks such as status queries, root-cause analyses or the identification of data gaps in road transport. In a next step, according to Shippeo, these agents are to deliver automated recommendations for executives that combine machine analyses with human decision-making authority.
Expanded features across multiple transport domains
In addition to Shippeo AI, the company unveiled further innovations of its platform. This includes a completely new eCMR system (Electronic Consignment Note), which replaces paper-based processes with digital real-time data. According to Shippeo, the new eCMR feature integrates compliance with legal requirements directly into existing workflows. It is intended to map the international eCMR standard, which is now used in more than 30 countries.
In the area of air freight, the Air-Visibility solution has been expanded. According to the company, all air transports can in the future be tracked in a unified view. Shipment information is automatically imported via Master Air Waybills and linked to existing transport
modes.
For finished vehicle logistics, Shippeo has further developed its Roll-on/Roll-off tracking solution. It covers more than 95 percent of the global RoRo fleet, according to the company. A new feature enables drivers to document transport damages via an app with time and location data.
Improved data quality and a new user interface
The platform itself has been technically revised as part of the extensions. According to the company, new flexible pairing modes, reduced required fields, and an improved data structure facilitate everyday use. In addition, the user interface has been redesigned. The new Global Map provides a 360° real-time view of worldwide logistics processes, including all seafreight vessels, and is intended to simplify route planning. The presentation of expected arrival times has also been revised to enable more precise forecasting and proactive disruption management.
„We know that most supply chain operators have so far not achieved a measurable ROI from their AI initiatives,“ explains Anand Medepalli, Chief
Product Officer at Shippeo. „That is why we are consistently betting on Useful AI. Shippeo AI turns those trusted data you rely on into intelligent, actionable insights. This allows teams under pressure to act faster, deploy their expertise more precisely, and ultimately work more productively.“
Background: Shippeo as a provider of multimodal transport transparency
Shippeo operates a platform for multimodal real-time transparency, which, according to the company, includes integrations to more than 228,000 freight forwarders and 1,100 systems in the areas of transport management, telematics, and electronic trip recording. Annually, around 100 million shipments are tracked via the platform in more than 150 countries.
Among the customers are internationally active industrial and commercial companies, including AkzoNobel, Barilla, Carrefour, Coca-Cola HBC, L’Oréal, LVMH, Renault Group, Saint-Gobain and Yamaha. The aim of the platform is to enable effective risk management, early disruption detection, cost optimization, as well as an increase in operational efficiency and a reduction of transport-related greenhouse gas
