LunaPath Introduces the AI Workforce for Freight, Eliminating $11.5B in Supply Chain Friction

Company expands beyond tactical automation to deliver specialized AI roles embedded directly into logistics teams.

CHICAGO, IL - February 26, 2026 - LunaPath today announced the expansion of its platform into a fully specialized AI workforce for freight operations, positioning the company at the forefront of a new model for logistics teams facing mounting margin pressure and labor constraints.

The announcement comes at a time when inefficiencies across freight execution are compounding into material economic impact. Drivers are detained an average of 173 hours per year, wait times exceed three hours on the majority of loads, and billions of dollars in detention charges go unrecovered. These inefficiencies ripple outward, affecting carrier economics, shipper rates, facility throughput, and ultimately consumer costs.

LunaPath’s AI workforce is designed to address these operational friction points directly.

Rather than layering another dashboard onto already fragmented systems, LunaPath deploys specialized AI roles that operate within existing workflows, coordinating appointments, communicating with carriers, validating documentation, managing exceptions, and updating systems of record in real time. Each agent is purpose-built for a narrow operational objective and embedded directly into the logistics team’s daily execution environment.

“Freight doesn’t have a visibility problem. It has an execution bottleneck,” said Abhishek Porwal, Founder of LunaPath. “For decades, teams have been forced to scale by adding people to chase updates, reschedule docks, reconcile paperwork, and manage exceptions. We built LunaPath to change that equation. Our AI workforce handles the repetitive, time-sensitive tasks so human teams can focus on decisions that actually move margin.”

The company’s expanded platform introduces specialized AI roles across the entire supply chain. Each role continuously monitors for operational risk signals, initiates structured outreach when conditions change, processes responses deterministically, and closes workflows automatically or escalates with full context when human judgment is required.

This workforce model reflects a broader shift in how logistics organizations are thinking about automation. Traditional tools surface alerts and require manual follow-up. General-purpose AI platforms promise flexibility but often lack domain precision. LunaPath’s approach is intentionally vertical, engineered specifically for freight operations and designed to integrate into existing TMS, YMS, and communication systems without requiring process replatforming.

We now have these 30 agents in action:

Over the Road

• Missing equipment IDs – source missing equipment IDs

• Unknown equipment IDs – resolve unknown equipment IDs submitted by carriers

• Invalid telematics connection – resolve telematics connections in ‘invalid’ status (e.g., bad credentials)

• Missing origin milestones – source missing origin milestones on shipments with visibility

• Missing destination milestones – source missing destination milestones on shipments with visibility

• Missed API tracked shipments – resolving missing visibility for API carriers

• Improper DriveView setup – resolving improper DriveView app configuration

• Enabling API carrier data feed – establishing PUSH data feed for existing API carrier

• Inactive Assets – resolving inactive assets not providing visibility

• Incomplete onboarding – resolving telematics onboarding gaps blocking visibility on active shipments

• Missing LTL delivery Out for Delivery – source missing delivery milestones on shipments with visibility

• Missing LTL Pickup milestones – source missing delivery milestones on shipments with visibility

• LTL appointment windows – source missing appointment windows

• TL connection - resolve tracking configuration issues for no tracking methods error

• TL - ingest appointment window updates from carriers at scale

• TL - update inactive contacts in Movement

• LTL Invalid API credentials – source and resolve LTL carrier credential issues

• Inbound carrier onboarding agent – answer troubleshooting questions

• Outbound carrier onboarding agent – engage carriers when onboarding stalls

• Reason code retrieval for running late TL shipments

• Proactive risk monitoring - Customs hold at discharge

Ocean

• Missing Ocean milestones – source missing picked up milestones not shared by forwarder

• Missing Ocean milestones – source missing delivery milestones not shared by forwarder

• Confirm booking for rolled containers

• Retrieve dwelling container location at the Port of Discharge

Warehouse

• Stock out risk - items are expected not to make it for the planned time

• Cross-dock allocation mismatch

• Prolonged dwell time (for multiple use cases like fraud, x-docks, detention, etc.)

• Cross-dock dwell - truck dwelling at x-dock and planned departure time has passed

The company reports that early deployments have reduced manual back-office tasks, improved throughput during disruption windows, and delivered measurable labor efficiency gains within weeks of activation.

As freight markets remain competitive and cost pressures intensify, LunaPath believes the future of supply chain execution will be defined not by more dashboards, but by embedded digital teammates capable of executing at scale.

“The next decade of logistics will not be won by who sees the most data,” added Abhishek Porwal, Founder of LunaPath. “It will be won by who acts on it fastest and most consistently. The AI workforce model is how freight teams get there.”

About LunaPath

LunaPath is the logistics industry’s AI sidekick, delivering affordable, specialized agents that automate grunt work, boost profitability, and scale operations without lock-in. With prebuilt playbooks across the supply chain, LunaPath slashes manual hours and cost per load in under a week.

Learn more at www.lunapath.ai.