Jett McCandless is building an AI-native supply chain, both organically and through acquisition.
The vision is clear: artificial intelligence that does not just analyze data or send alerts, but manages exceptions, optimizes routing, handles negotiations, and resolves problems without waiting for a human to step in. The acquisition of LunaPath.ai, announced April 9th, 2026, is a concrete move in that direction.
The Chicago-based leader in supply chain decision intelligence bought LunaPath in an all-cash deal. LunaPath builds AI-native agents made specifically for logistics execution and orchestration. These agents do not just handle tasks in isolation. They coordinate across workflows, connecting systems, carriers, and operational context to drive resolution at scale. The high-volume, repetitive work that still burns hours across phone, email, and daily operations is exactly where they operate.
This is not another supply chain tool. It is about moving from scattered insights to real-time autonomous action grounded in actual operational context.
From Data Graph to Agentic Execution
project44 has spent more than a decade building what they call the world’s largest and most accurate real-time logistics data graph. It pulls together disconnected systems like ERP, TMS, visibility platforms, yard management, and others into one unified model of how freight actually moves.
LunaPath’s agents now connect directly into that graph. They are not guessing. These agents understand what is happening with a shipment, why it matters, and what action makes the most sense. They manage carrier check calls, pull proof of delivery, start claims, confirm appointments, and fix exceptions the way a seasoned logistics pro would. They prioritize based on real downstream impact.
Jett McCandless and his team have been piloting different AI platforms for the past few years. They found LunaPath did the job better than the rest. The team says LunaPath has a much more efficient model, largely because of how it was trained for logistics workflows.
“We are building native AI solutions rather than trying to bolt AI onto legacy technology,” McCandless said. “It rarely works as advertised.”
He hears the same thing from clients repeatedly. There are plenty of AI tools on the market, but most fail to deliver because the AI was never built into the application from the start. project44, he noted, is the database of record for transactions, which makes the whole system smarter with every shipment that moves through it. The company now handles 4.6 million shipments a day. That volume makes the model far more robust and turns automation into something that actually works at scale.
For global clients in particular, he noted that email is far more reliable than voice. AI still struggles with local languages, dialects, and especially industry jargon. Email avoids those problems and performs much better for consistent execution.
This is project44’s second major AI-focused acquisition after ClearMetal in 2021. Since then, their AI has already improved predictive ETAs, given deeper order-level visibility, and helped spot disruptions before they hit. LunaPath takes it further by turning intelligence into actual real-time execution.
A Multi-Vendor Orchestration Strategy That Makes Sense
project44 is not putting all its chips on one big AI model. They are building an orchestration layer that runs on their supply chain data graph. Specialized agents like LunaPath for execution, plus partners such as Vooma and HappyRobot, each do what they do best. Everything stays under one Decision Intelligence Platform with unified control.
Over 16 months, project44 tested eight different AI agent providers in live operations. LunaPath stood out for high-volume voice and messaging work and fit smoothly into the platform.
McCandless believes the future of AI in logistics needs technology that is built for the AI age from the ground up, not just an agent slapped on top. Because project44 had to develop its core technology as AI-native early on due to the massive scale of its implementations, it now has a real competitive edge.
“Ultimately, the AI that sits on top of the client’s data will automate exception management, routing, negotiation, and find solutions without needing human interference,” he said. The goal is to help companies put in place a truly AI-native supply chain.
Jonathan Scherr, Chief Strategy and Operations Officer at project44, put it this way: “AI without context creates noise, not outcomes. What makes project44 different is the supply chain graph we have built over more than a decade. It gives AI agents the context they need to act with precision. LunaPath brings execution into that graph and turns intelligence into real-time action.”
Abhishek Porwal, founder of LunaPath, said: “We built LunaPath to automate the operational work that slows logistics teams down. project44’s supply chain data graph gives our agents the context they were missing. Together, we are enabling AI that does not just recommend what to do but understands when and how to do it.”
Real-World Impact for Shippers and Operators
Joshua Moss, Global Supply Chain Center of Excellence Manager, said project44’s AI has helped keep strong visibility across their carrier network even as things constantly change. It has even let them expand confidently into APAC with less technical carriers without adding extra operational headaches.
In freight, missed pickups, document gaps, and appointment changes quietly eat into margins. Agents that actually fix these problems instead of just flagging them can bring fast returns. LunaPath claims measurable gains in cost per load and faster resolution times.
The Bigger Picture for Freight
Supply chain tools are finally moving past dashboards and alerts toward systems that actually get the work done. They are built for AI from the start instead of just patched on later.
AI is coming to freight and logistics as providers recognize the power of the technology and significant improvements offered to clients. Plus, without it, clients have little incentive to shift to a new offering. P44’s native approach toward AI-native technology gives it a massive advantage over legacy rivals, especially as companies prioritize AI for its speed, cost efficiencies, and the ability to eliminate redundant tasks.
project44 helps clients move over 1.5 billion shipments a year for more than 1,000 big brands in manufacturing, retail, automotive, life sciences, and other sectors. Adding execution-focused agents on top of native AI and that daily volume of 4.6 million shipments could cut a lot of the manual work that still drags on operations.
LunaPath brings more than 50 purpose-built agents and ready-made playbooks. Paired with project44’s contextual graph, the result is a system where AI does not just point out problems. It helps solve them in real time with the right priorities.
These agents will not replace human judgment on tough exceptions or relationship-sensitive decisions. But they will absorb the high-volume repetitive tasks that tie up teams today and free people up for more important work.
The acquisition strengthens project44’s position as a Decision Intelligence Platform spanning Transportation Management, Visibility, YMS, and Ecommerce Logistics, and now adds the AI execution layer that turns all of it into autonomous action.
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