project44, the leading Decision Intelligence Platform for the modern supply chain, announced a revolutionary portfolio of AI agents designed to automate the most complex and critical tasks within shipper operations.
Spanning every mode and node of the global supply chain-from manufacturing facilities to the last mile, and from ocean transit to over-the-road freight-these agents are engineered to reduce freight spend, accelerate exception resolution, lower inventory carrying costs, and drastically improve on-time performance.
While many enterprise AI initiatives struggle due to weak data foundations, project44’s agents are built on a decade of normalized, real-time logistics data. This foundation provides the deep semantic understanding required for agents to not only process information but to make high-stakes operational decisions with human-like reasoning.
“Supply chain teams are under real pressure, and the work that drains capacity is rarely the work that requires human judgment,” said Jett McCandless, Founder and CEO of project44. “What we have built is not just a set of agents. It is context, skills, and an orchestration that coordinates across our own agents and the broader ecosystem, always grounded in the world’s largest, most accurate and real-time logistics data graph. Customers should not have to pick the best agent vendor. We do that for them. The result is a supply chain that acts on the best available intelligence, continuously, at global scale, getting closer every day to running on autopilot.”
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Targeting High-Impact Operational Challenges
The project44 AI agent portfolio addresses specific, high-cost “jobs to be done” that have traditionally relied on manual, error-prone effort. The specialized agents include:
Freight Procurement Agent: Benchmarks contracted rates against live market conditions in real-time and automates carrier selection to eliminate manual bid cycles.
Disruption Management Agent: Monitors global events and maps their specific impact on a shipper’s network to initiate proactive responses before exceptions escalate.
Network Operations Agent: Resolves visibility gaps automatically by monitoring carrier connectivity and equipment ID accuracy, ensuring a “self-healing” data stream.
Disruptions Management Agent: Identifies and resolves interruptions like failed pickup attempts or route changes for all transportation modes to minimize dwell times.
Scheduling Agent: Automates inbound and outbound appointments to maximize dock capacity and minimize inventory holding costs.
Carrier Onboarding Agent: Accelerates network growth by engaging with carriers around the clock autonomously, significantly minimizing the carrier onboarding process duration.
Proven Impact at Scale
Early adoption data reveals a significant appetite for autonomous execution. Since deployment, agent-driven interactions have surged 60x, growing from 500 to over 30,000 weekly interactions. To date, these agents have executed nearly one million automated communications, improving data quality by 30% and slashing issue resolution times by 75%.
The Three Foundations: Context, Skills, and Orchestration
project44’s multi-agent architecture is defined by three pillars that cannot be replicated by simply upgrading a large language model (LLM):
Context: Powered by the world’s largest logistics data graph, connecting 259,000+ carriers across 186 countries and processing 700 million daily events.
Skills: Each agent possesses a “skill”-a combination of narrowly defined tasks and a semantic layer that understands exactly what data like “on-time” means for a specific customer.
Orchestration: An advanced orchestration layer determines the order in which processes should be run, indicating which agents need to be triggered and which processes require intervention by humans. An audit trail of all activities undertaken is maintained.
In moving away from a reactive dashboard approach towards an autonomous one, project44 is helping the world’s most powerful brands move with an unprecedented level of agility in today’s ever-changing global landscape.
