Shipsy, an AI-native enterprise logistics management platform, announced the beta launch of Shipsy Brain, a logistics native intelligence layer.
Shipsy Brain helps enterprises orchestrate decisions and execute operational workflows with considerably greater accuracy, speed, and control over frontier AI models
Shipsy Brain combines specialized open source models with logistics data generated through Shipsy's platform.
That includes:
● 50 billion+ operational events recorded over five years.
● 1 billion+ autoassigned decisions and 500 million+ human decisions, along with reassignment history.
● 100 billion+ GPS location pings connected with route and delivery outcomes.
● 3 billion+ delivery labels across different carriers and formats.
● 342 carrier integrations and more than 50 million routing decisions.
● 3 billion+ hub scans covering the movement of shipments through the network.
● 5,000+ workflows built across Shipsy's Workflow Builder and AgentFlow platform.
This data enables Shipsy Brain to understand logistics specific context that may be ambiguous to a general model.
Shipsy Brain is designed as a central intelligence layer coordinating specialized models for areas such as documents, consignments, trips, workflows and finance. These models can power agents for document validation, address intelligence, anomaly detection, ETA prediction, routing, settlement management and workflow recommendations
It lives inside Shipsy’s AgentFleet platform, where it watches live operations, identifies manual work it can automate, requests permission, and self-executes gated by its confidence on each specific action. When a human corrects it, it learns from the correction, so the platform improves from what it runs.
It is model agnostic. Any model connected to it gains access to the full operational context which means every general improvement in AI models makes Shipsy Brain more useful.
