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Shipsy Launches AI Intelligence Layer for Logistics
WAREHOUSING & LOGISTICS

Shipsy Launches AI Intelligence Layer for Logistics

Shipsy, an AI-native enterprise logistics management platform, has launched the beta version of Shipsy Brain, a logistics intelligence layer designed to help enterprises improve decision-making and automate operational workflows.

Built on specialised open-source models and logistics data generated through Shipsy’s platform, Shipsy Brain enables AI agents to understand operational context and execute actions with greater accuracy, speed and control compared to general AI models.

The intelligence layer is powered by more than five years of logistics data, including over 50 billion operational events, 1 billion+ auto-assigned decisions, 500 million+ human decisions, 100 billion+ GPS location pings, 3 billion+ delivery labels, 342 carrier integrations and billions of hub scans.

Shipsy Brain acts as a central intelligence layer connecting specialised models for documents, consignments, trips, workflows and finance. These capabilities support AI agents across use cases such as document validation, address intelligence, anomaly detection, ETA prediction, route optimisation, settlement management and workflow recommendations.

Integrated within Shipsy’s AgentFleet platform, Shipsy Brain monitors live operations, identifies automation opportunities, seeks approval where required and executes defined actions based on confidence levels. The platform also learns from human corrections, enabling continuous improvement of operational decisions.

According to Shipsy, the model-agnostic architecture allows connected AI models to access logistics-specific operational context, helping enterprises benefit from advancements in AI technologies while maintaining business controls.

The company said Shipsy Brain delivers improvements across accuracy, speed and cost efficiency by using logistics-trained models instead of relying entirely on expensive general-purpose AI models. Specialised models require fewer computing resources and help enterprises achieve more predictable AI deployment costs.

Shipsy highlighted that its logistics-focused models have demonstrated stronger performance in document intelligence benchmarks, achieving an 86.6% score in document understanding compared with earlier benchmark results from general AI models.

Shipsy Brain is currently available in beta for select enterprises and is aimed at helping businesses move from AI-assisted dashboards towards intelligent systems capable of reasoning, recommending and executing logistics decisions.

Shipsy, an AI-native enterprise logistics management platform, has launched the beta version of Shipsy Brain, a logistics intelligence layer designed to help enterprises improve decision-making and automate operational workflows.Built on specialised open-source models and logistics data generated through Shipsy’s platform, Shipsy Brain enables AI agents to understand operational context and execute actions with greater accuracy, speed and control compared to general AI models.The intelligence layer is powered by more than five years of logistics data, including over 50 billion operational events, 1 billion+ auto-assigned decisions, 500 million+ human decisions, 100 billion+ GPS location pings, 3 billion+ delivery labels, 342 carrier integrations and billions of hub scans.Shipsy Brain acts as a central intelligence layer connecting specialised models for documents, consignments, trips, workflows and finance. These capabilities support AI agents across use cases such as document validation, address intelligence, anomaly detection, ETA prediction, route optimisation, settlement management and workflow recommendations.Integrated within Shipsy’s AgentFleet platform, Shipsy Brain monitors live operations, identifies automation opportunities, seeks approval where required and executes defined actions based on confidence levels. The platform also learns from human corrections, enabling continuous improvement of operational decisions.According to Shipsy, the model-agnostic architecture allows connected AI models to access logistics-specific operational context, helping enterprises benefit from advancements in AI technologies while maintaining business controls.The company said Shipsy Brain delivers improvements across accuracy, speed and cost efficiency by using logistics-trained models instead of relying entirely on expensive general-purpose AI models. Specialised models require fewer computing resources and help enterprises achieve more predictable AI deployment costs.Shipsy highlighted that its logistics-focused models have demonstrated stronger performance in document intelligence benchmarks, achieving an 86.6% score in document understanding compared with earlier benchmark results from general AI models.Shipsy Brain is currently available in beta for select enterprises and is aimed at helping businesses move from AI-assisted dashboards towards intelligent systems capable of reasoning, recommending and executing logistics decisions.

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