Project44 unveils fleet of AI agents at customer event Decision44

On April 9, 2026, Project44 CEO Jett McCandless stood before customers at the company’s Decision44 event and delivered a sweeping history lesson that doubled as a mission statement.

From the agricultural surplus of 10,000 BC that enabled civilization, to Rome’s maritime empire, the Silk Road’s intermediaries, the compass that unlocked ocean navigation, the 13th-century bill of lading, the printing press and the standardization of information, railroads (and the invention of time zones), electricity, the telegraph, the 1956 shipping container that slashed loading costs from 58.

6 cents to 16 cents per ton, and the birth of EDI during the Berlin Airlift, every major transformation, McCandless argued, produced a new supply chain model as its primary consequence, not a side effect. “What if their systems moved at the speed of thought?”

McCandless asked, framing the current moment as the culmination of 12,000 years of human logistics breakthroughs. In the 1990s, the internet brought retail and finance into real-time data, “but logistics kept picking up the phone,” he said. When McCandless entered the industry in 1999, it still ran on phones, faxes, emails and AS/400 systems.

“The hardest working people in the world” were making million-dollar decisions with partial information because their systems failed them. The real constraint, McCandless insisted, was never human effort—it was the systems around the humans. Project44’s 2014 founding was an attempt to fix that. The company spent a decade and $1.

5 billion in R&D to build what McCandless called the connective tissue the global supply chain lacked: “We turned the lights on.”

The result was visibility at unprecedented scale and a logistics data graph that captured more than 1 billion customer-created events per day and 4 petabytes of data monthly, the equivalent of watching YouTube 24/7 for 9,000 years. But visibility brought chaos and analysis paralysis. The signal-to-action ratio was just 2 percent.

The industry became informed, yet frozen. “What if this is as far as we go?” McCandless recalled asking himself. “What if we gave the world a clear view of its problems, but we can’t solve them fast enough?” The answer, unveiled during Decision44, is a new class of AI agents that collapse the three-step lead time—truth, decision, action—into a single motion.

A process that once took days now takes seconds. “Agency is a dial you control,” McCandless said. The technology is no longer the bottleneck. The last remaining constraint is the processes built around it: every approval chain, sign-off and “let me see.” The hardest part of what comes next “isn’t technology… it’s new processes.”

Building trusted AI for the supply chain Chief Strategy Officer and Chief Operating Officer Jonathan Scherr picked up the thread, declaring the company’s mission unchanged—“to eliminate friction from global trade”—but now executed through AI that enterprises can actually trust.

McKinsey estimates AI’s enterprise impact at $8 trillion annually, yet only 1 percent of global enterprises consider their AI mature. In supply chains, where the cost of failure is measured in lost cargo, stockouts or detained trucks, trust is the gap. Scherr broke trust into three pillars: Data, Intelligence (logic and reasoning), and Action.

Large language models like Claude, GPT or Gemini are powerful at collating public data, but insufficient alone for business use cases. “The data that sits on top of the LLM… is what makes it valuable,” he said.

Project44 calls this “context”: the situational knowledge of relationships between pieces of information that lives mostly outside any single organization. More than 80 percent of AI implementations fail because of insufficient context, Scherr noted.

Project44’s decade-long investment in its data graph, interoperability with WMS, TMS, YMS, ERP and OMS systems, and AI agents that proactively reach out to carriers (via the recent LunaPath acquisition) have already delivered measurable gains: more than 25 percent improvement in ETA accuracy.

The company is now embedding “context-fueled intelligence” directly into the platform. Supply chain has its own semantics—“on-time” means something different to every organization—and the system must understand pattern recognition and reasoning.

Scherr introduced “Mo,” a context-aware chatbot coming in early July that lets customers upload their own shipment history, business rules and semantic layer for true analysis grounded in their data.

From Autopilot to specific agents: p44’s product roadmap Nick Ruggiero, director of product management for Autopilot, detailed how Project44 is turning that intelligence into automated, trusted workflows.

The agents are configurable, explainable and human-controlled, with granular controls, transparent logic, audit history and intervention points at every critical step. Stored workflows function like a prompt library. Early results: 17 percent reduction in manual exception handling. Configurable