By Kris Glotzbach, Chief Revenue Officer, LunaPath As I prepared for the recent webinar with project44 , I spent time reflecting on the questions I hear most often from supply chain leaders: What actually makes AI agents different from the last wave of automation? Why does adoption stall in so many organizations? And why does this moment feel different? The short answer is this: we’ve reached an inflection point where visibility alone is no longer enough. The next phase of va

The Track & Trace Problem Operations Leaders Know Too Well Track and trace should be straightforward. In practice, it's one of the most time-consuming workflows in freight operations. Even with visibility platforms and ELD data, operations teams spend hours each day on: Calling drivers for ETAs Following up on missed milestones Clarifying delay reasons Manually updating systems Responding to "where's my load?" customer inquiries The real issue isn't missing data. It's the la

In freight operations, cost per load is the clearest reflection of operational health. It captures labor efficiency, process maturity, technology leverage, scalability, and margin resilience. Revenue can fluctuate with the market. Cost per load determines whether you survive it. As freight margins compress, operations leaders face mounting pressure to reduce cost per load without sacrificing service, burning out teams, or re-platforming systems. This is where AI automation is

In Project44’s “Agents in Action” webinar , Mark Strassman (Chief Product Officer, Project44) moderated a practical, production-focused panel with Jesse Buckingham (Founder, Vooma) , Pablo Palafox (Co-founder & CEO, HappyRobot) , and Kristopher Glotzbach (CRO, LunaPath) . The conversation was refreshingly direct: AI agents are no longer a “do they work?” question. Now it’s “how do we deploy them effectively?” Below is a summary of the most actionable lessons for shippers, 3PL

Why Multi-Agent Architectures Are Becoming the Standard As freight automation matures, leading logistics organizations are converging on the same realization: No single AI system can handle the full complexity of freight operations. Instead, the most effective teams are building multi-agent freight automation stacks - systems where specialized AI agents work together, coordinated by orchestration logic and overseen by humans. This approach mirrors how logistics teams already

The Question Every Freight Leader Is Asking As AI adoption accelerates across logistics, one debate keeps coming up: Should we deploy one powerful "super-agent" that handles everything, or multiple specialized AI agents designed for specific tasks? The super-agent sounds appealing - one system, one interface, one brain. But in freight operations, focus consistently beats breadth. This post explains why specialized AI agents outperform generalist "super-agents" in freight auto

Picture this: It's 3 PM on a Thursday, and your team has already made 47 check calls today. They've sent 128 emails asking for ETAs. They're waiting on PODs from 23 different carriers. And someone just walked into a meeting saying, "We lost visibility on the Phoenix delivery." This is the daily reality for freight brokers and 3PLs across the country. Carrier communication isn't just time-consuming; it's the operational bottleneck that determines whether you deliver exceptiona

AI adoption in US logistics has accelerated dramatically over the past 18 months. Not because of hype, but because AI agents have finally become practical, accurate, and reliable enough to handle real operational work. Today, US freight operators are deploying AI to automate tasks that were historically done manually by brokers, carrier reps, CSRs, and back-office teams. The results are dramatic: lower cost per load , faster cycles, fewer errors, and teams freed to focus on

Document collection is one of the most frustrating bottlenecks in freight operations. PODs stuck in email threads. Lumper receipts that never arrive. Carriers who forget to upload. Billing cycles that drag on for days. Customer service teams fielding "where's my proof?" calls. If you run a brokerage, you know the reality: document collection is high-volume, time-sensitive, and painfully manual. AI is changing that. Why Document Collection Is Perfect for AI Document workflows

Logistics teams are under constant pressure: more shipments, tighter SLAs, rising customer expectations, and shrinking margins. Across brokerages, 3PLs, and shipper operations teams, leaders ask the same foundational question: "How do AI agents actually improve logistics team efficiency?" This guide breaks the answer down clearly using real workflows, operator-driven insights, and practical examples. No hype. No theory. Just how AI agents make teams faster, more accurate, and

Freight brokers, 3PLs, and shippers are all facing the same pressure heading into 2025: do more with less, reduce cost per load, improve customer SLAs, and scale without hiring. AI agents are now the fastest path to that outcome. This year, the freight tech market finally matured enough to deliver real automation - not demos, not hype. This guide breaks down the best AI agents for freight in 2025, the problems they solve, and where they fit in your tech stack. You'll also lea

This Isn't Really a Competition As AI tools flood into freight and logistics, you're probably seeing more platforms promising to "automate everything." But not all AI is built the same way, and that's actually a good thing. Two distinct categories are emerging: Tactical AI agents that do one job extremely well (like LunaPath) Generalist AI platforms that coordinate across many workflows (like CloneOps) Here's the thing: these aren't competing approaches. They're complementa

Why This Matters When logistics teams adopt automation and AI, they're trusting new technology with their most sensitive data. Load information. Customer details. Payment records. Operational metrics. Security and compliance aren't optional; they're foundational. That's why LunaPath is AICPA SOC certified, a globally recognized standard for data security, system reliability, and organizational trust. What Is AICPA SOC Certification? The American Institute of Certified Public

The Bottom Line (For Busy IT & Ops Leaders) No re-platforming required. LunaPath connects to your existing TMS and visibility stack via APIs, webhooks, and secure mailboxes. Your system of record stays your system of record. Our agents write back clean, validated data; no shadow databases. Security first. SOC-aligned controls, role-based access, encryption, and audit trails for every action. Built-in guardrails. Clear scope, human-in-the-loop escalation, rate-limited outr

(Webinar Recap) TL;DR Agents ≠ chatbots. True agents decide, reason across multiple steps, and take actions across systems. Value compounds with orchestration. The Agent Maturity Curve moves from single-task agents → multiple agents → agents that coordinate and share context. Readiness matters: data quality, connected systems, and continuous learning determine outcomes. Trust is designed, not assumed: disclosure, rate-limited outreach, language adaptability, audit trails,

Artificial intelligence isn’t on the horizon for freight it’s already in the cab, the control tower, and the TMS. From predictive analytics to automated communication, AI is streamlining logistics operations and closing long-standing efficiency gaps. But the real transformation isn’t coming from broad, “do-everything” systems; it’s coming from focused AI agents that handle specific, repetitive tasks faster and more consistently than humans ever could. According to a recent

AI is becoming an everyday part of freight operations. It's being used to make calls, retrieve documents, send updates, and write directly into TMS systems. But as adoption accelerates, one question keeps coming up: " How do we stay in control? " For AI to scale responsibly in freight, it needs more than performance. It needs guardrails. Clear policies, permissions, and auditability ensure automation doesn't just work fast, but it works right. At LunaPath, we believe the winn

Every major shift in logistics follows the same pattern: new tools handle the heavy lifting, and people move up the value chain. Forklifts didn't replace warehouse workers. They made them more productive. TMS systems didn't replace dispatchers. They helped them manage more freight with fewer errors. Now it's AI's turn. Tactical AI agents are forklifts for data. They lift the repetitive, time-sensitive work that clogs operations. Meanwhile, humans steer by making judgment call

In freight brokerage, every minute matters. And every manual task adds up. Labor represents nearly 40% of brokerage expenses, over $30 billion annually across the U.S. truckload market. With margins already tight, even modest efficiency gains can meaningfully reduce your cost per load. AI automation is changing that equation. Instead of requiring expensive platform overhauls, tactical AI agents eliminate the repetitive, time-consuming work that bogs down your team. Understan

The logistics industry stands at a critical inflection point. Traditional dispatch operations and business process outsourcing (BPO) models that dominated for decades are giving way to AI-powered logistics automation . At LunaPath, our decades of combined expertise in freight technology and operations have positioned us to lead this transformation. The Evolution of Freight Dispatch Operations Brokerage dispatch operations have undergone several transformations over the past t