project44 Acquires LunaPath.ai to Build Autonomous Supply Chains

CHICAGO, IL – April 09, 2026 – Supply chain intelligence leader project44 today announced its acquisition of LunaPath.ai, an AI-native logistics automation company, in an all-cash transaction. The move signals a pivotal shift in the industry, accelerating project44’s strategy to move beyond predictive visibility and create supply chains that can autonomously execute complex operational tasks.

This acquisition embeds LunaPath’s specialized execution agents directly into project44’s Decision Intelligence Platform, aiming to eliminate repetitive freight work and translate data-driven insights into coordinated, real-time action. The deal marks project44’s second major strategic AI acquisition, following its landmark purchase of predictive intelligence firm ClearMetal in 2021, underscoring a long-term vision to build a truly automated, self-correcting logistics ecosystem.

From Insight to Autonomous Action

For years, the holy grail of supply chain technology has been real-time visibility—the ability to see where freight is at any given moment. With this acquisition, project44 is making a definitive statement that seeing is no longer enough. The new frontier is autonomous action, where AI doesn’t just report a problem but actively works to solve it.

LunaPath.ai specializes in creating purpose-built AI agents designed to handle the high-volume, low-value tasks that consume countless hours for logistics operators. These agents can autonomously manage a full range of operational workflows, from making carrier check calls and retrieving proof-of-delivery documents to initiating claims and confirming freight appointments across email, voice, and messaging platforms. By integrating these capabilities, project44 aims to close the gap between intelligence and execution that plagues many organizations.

This evolution is already resonating with customers who manage vast and dynamic logistics networks. “project44 already gives us strong visibility across our carrier network,” said Joshua Moss, Global Supply chain Center of Excellence Manager. “Their AI capabilities protect that visibility by staying ahead of the constant change that comes with managing a global carrier base. Connections shift, carrier setups evolve, and keeping everything in sync at scale used to take real effort. Before the deployment of project44’s AI agent, we had minimal visibility into the APAC region. It's allowed us to expand confidently into APAC and bring less technical carriers into the fold, without adding operational complexity.”

Solving the Critical 'Context Problem'

Most AI applications in the supply chain have struggled to deliver on their promise because they lack one crucial ingredient: context. Logistics data is notoriously fragmented, living in disconnected silos across ERPs, transportation management systems (TMS), and various partner platforms. Without a unified view, AI can generate more noise than meaningful outcomes.

project44’s core strategy hinges on solving this context problem. Over the past decade, the company has built what it calls the world's largest and most accurate logistics data graph, which unifies systems, partners, and events into a single contextual model of how freight moves. The acquisition of LunaPath is designed to weaponize this context.

“AI without context creates noise, not outcomes,” said Jonathan Scherr, Chief Strategy and Operations Officer at project44. “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, turning intelligence into real-time action across the supply chain.”

LunaPath’s agents will now operate within this rich contextual model. Grounded in live shipment data and historical performance patterns, the agents can understand the downstream impact of a delay or an exception before acting. This enables them to prioritize, escalate, and resolve issues with the nuanced judgment of an experienced logistics professional, but at a global, automated scale.

“We built LunaPath to automate the operational work that slows logistics teams down,” said Abhishek Porwal, founder of LunaPath. “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.”

A Strategic Move in a Competitive AI Arms Race

The acquisition is also a calculated move in an increasingly competitive market where major logistics technology providers are racing to integrate more advanced AI. Competitors like FourKites and Shippeo have also announced their own AI agent strategies, signaling a clear industry-wide push towards automation and orchestration. However, project44 is differentiating itself through a multi-vendor, best-of-breed approach.

Rather than relying on a single, monolithic AI, the company’s AI Agent Orchestration strategy involves coordinating a variety of specialized agents—including those from partners like Vooma and HappyRobot—through its centralized data graph. This allows customers to deploy the highest-performing agent for each specific job while maintaining unified governance and analytics.

The selection of LunaPath was the result of a rigorous 16-month evaluation where project44 assessed eight different AI agent vendors in live supply chain environments. LunaPath consistently delivered standout performance, particularly in high-volume voice and messaging execution, making it a critical component of project44’s ecosystem.

“LunaPath is exactly the kind of specialized, high-performing agent that makes our orchestration vision real,” said Jett McCandless, Founder and CEO of project44. “We take a best-of-breed approach, selecting the highest-performing agents for the workflows they execute best and bringing them together to operate as one system. LunaPath brings execution into that system, pairing real-time action with domain expertise.”

The Dawn of the Self-Executing Supply Chain

This acquisition represents more than just a new feature set; it marks a step toward a new paradigm for global logistics. The concept of an autonomous supply chain—one that can sense disruptions, make intelligent decisions, and execute solutions without human intervention—is rapidly moving from a futuristic vision to a practical reality.

The implications for the industry are profound. Automating routine tasks is expected to drive significant efficiency gains, lower operational costs, and free human talent from the drudgery of manual follow-ups and data entry. The role of the supply chain professional is set to evolve, shifting from a tactical operator to a strategic orchestrator who manages the AI agents, handles high-level exceptions, and focuses on improving the overall system.

As AI-powered automation becomes more deeply embedded in core logistics functions, companies will be able to operate with greater agility and resilience in the face of constant disruption. This integration of contextual data with autonomous execution promises a future where global supply chains are not just visible, but intelligent, adaptive, and increasingly self-managing.