FreightX

Freight runs on thousands of messy emails and texts a day, and the only way the industry has found to keep up is hiring more people every time volume grows.

FreightX treats the inbox as a database, with agents that read, classify, and act on every freight email across portals, voice, and the TMS, cutting manual work by 70 to 85 percent and letting a team handle several times the shipments without growing in lockstep.

The situation

Freight operations run on communication, and most of it is unstructured. A single team fields thousands of emails a day, plus a scatter of carrier portals and systems that do not talk to each other, and someone has to read all of it and key the important parts into the right place by hand. Claims, delivery appointments, proof-of-delivery requests, carrier negotiations, all of it arrives as free text and gets processed manually. The industry has quietly accepted this as the cost of doing business, which is why headcount grows in lockstep with shipment volume. Handle more freight, hire more people. The work does not scale, so the team just gets bigger and the margins get thinner.

Why it was hard

The obvious approach, a set of rules that scans emails for keywords, falls apart on contact with reality. Freight email is endlessly varied. Every carrier, broker, and shipper writes differently, the same request shows up in a hundred formats, and the important detail is often buried in a forwarded thread or an attachment. Pulling reliable, structured data out of that mess, a claim, an appointment time, a document request, without getting it wrong, is the first hard part, and errors are expensive, since a missed appointment or a misfiled claim carries real downstream cost. The second is that reading is not enough. The work only counts when something happens across the systems involved, email, voice, carrier portals, and the transportation management system that serves as the system of record, none of which share a clean interface. Doing all of that reliably, without a human checking every step, is the real problem.

The approach

FreightX treats email as a database rather than a to-do list. A set of agents reads every incoming communication, classifies what it is, and extracts the actionable data inside, the claim, the appointment, the proof-of-delivery request, the carrier negotiation, turning free text into structured records. TheAgentic Reasoning Workbench then decides what each one requires and orchestrates the response across the systems that matter, email, voice, carrier portals, and the transportation management system, so the task is not just understood but completed. The reasoning-enhanced build uses the Sanscritic engine for reliable retrieval across long, messy threads and prior context, so an agent acting on a message has the full history behind it rather than a single email in isolation. The result is a loop that runs without a person keying data between systems.

What happened

The change is structural, not incremental. Manual work drops by 70 to 85 percent, because the reading, extracting, and system updates that used to eat a person's day now happen automatically. And because capacity is no longer tied to headcount, a team can handle three to five times the shipment volume without growing at the same rate, breaking the link the industry had accepted as permanent. The work that remains for people is the judgment and the exceptions, not the data entry. FreightX is being built and validated with design partners in freight and logistics, where the volume is relentless and the manual baseline is exactly the cost everyone assumed was unavoidable.

What this means for you

If you run freight operations, you know the trap. More volume means more headcount, forever. The bottleneck was never your team's capability. It was the thousands of unstructured messages and disconnected systems standing between a communication and a completed action. That is what FreightX removes, and it is the shape of what becomes possible when deep logistics expertise and agent infrastructure are built together.