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Consulting · Freight forwarders

AI transformation for freight forwarders

We start by mapping what is actually worth automating, then build the data infrastructure, dashboards, and AI agents that turn a forwarder into a data-native operation. Implementation has an end date — year-two cost goes to zero.

  • Cargowise-native: integrations and extracts that respect your support agreement.
  • Rating-system-fluent: 7LFreight, MercuryGate, and CargoSphere on day one.
  • AI-first: agents that talk to your real systems, not toy demos.
  • Implementation that ends: year-one build + training, year-two cost goes to zero.

The gap

It is not a technology problem. It is a strategy problem.

Most forwarders already have the raw material — Cargowise, rating systems, accounting, even some AI. The problem is that it is siloed, pointed at the wrong tasks, and unmeasured. That gap — not the technology — is why most AI efforts stall, and it is what everything below is built to close.

Start hereThe entry point

AI & Data Strategy Roadmap

A fixed-scope diagnostic that maps which workflows AI should (and should not) touch, audits whether your data is actually ready, and defines the KPIs we will move — before you commit to a single build.

  • Workflow map (the jagged frontier)
  • Data-readiness audit
  • KPIs & sequenced roadmap

Automate the busywork

Point AI agents at the repetitive, well-defined work — quoting, cross-system tasks, and inbound calls.

How we work

  1. 1

    Phase 1

    Discovery

    We map your systems, your data, your team, and the questions leadership keeps asking that no dashboard answers today.

  2. 2

    Phase 2

    Foundation

    Stand up the BI stack and the data warehouse. Get the data flowing reliably before anything intelligent runs on top of it.

  3. 3

    Phase 3

    Intelligence

    Build the dashboards, then layer the AI agents on top. Each piece earns its keep before we move to the next.

  4. 4

    Phase 4

    Handoff

    Train your team, document everything, stand down. We stay on call for major upgrades; we do not bill for our absence.

FAQ

Why specifically freight forwarders?

Because the data problems are unusually well-shaped: Cargowise is universal, the rating systems are a known set, the KPIs are consistent across companies, and AI agents have a clear ROI surface (quoting, ops exceptions, customer service). We can move faster here than in industries we are learning from scratch.

What size of forwarder do you work with?

Sweet spot is $20M–$500M in revenue. Below $20M the implementation cost usually outweighs the ROI; above $500M you typically have internal teams that can lead this work, and we play a different role (advisory, audit, specific integrations).

How do you price an engagement?

Fixed-price per service, with a clear scope and end date. We do not bill hourly because hourly billing creates the wrong incentives — we want to ship, hand off, and exit. Implementation team cost goes to zero after year one except for major upgrades.

Can we start with one service and add more later?

Yes — most engagements start with the AI & Data Strategy Roadmap, which names the highest-ROI place to begin and the order to expand in. From there, teams typically build the data foundation or the rating-system agent first and grow once we have proven results inside your business.

Do you work with non-forwarders?

Selectively. The patterns transfer to customs brokers, 3PLs, and trucking carriers; we will scope an engagement if the data shape is close enough to forwarders. We turn down work that is too far from our core competence.

Ready to talk specifics?

Pick a service, pick a time. We will tell you in 30 minutes whether this is a fit.

Book a consultation