Code Quarry

Transportation & Logistics

AI employees for the work around your logistics systems.

3PLs, fulfillment operations, brokerages, carriers, drayage, intermodal, and warehousing run on systems that do their job. The WMS does its job. The TMS does its job. Code Quarry builds AI employees that handle the operational work happening around them, the work your people are doing between them today.

Built for
  • 3PLs
  • Fulfillment
  • Freight brokerages
  • Asset-based carriers
  • Drayage & intermodal
  • Warehousing

The systems involved

One process usually spans several of these.

WMS
TMS
Email & phone
Customer portals & EDI
Carrier & driver communication
Documents
Billing & AR

Plain boxes on purpose. These are yours, and they stay where they are.

The work between them

  • Reading incoming email to work out what a customer actually changed.
  • Re-keying order, load, and shipment details from one system into another.
  • Investigating exceptions and deciding who needs to know about them.
  • Chasing missing documents and details before work can move or bill.
  • Coordinating with customers, carriers, and facilities to keep things moving.

This work scales with volume, not with software. Every order and every load adds more of it, which is why the answer has always been another coordinator. The operations we help are the ones carrying several people doing this by hand, where that headcount is growing faster than margin.

Where we start

Where we build first.

Your transportation software does its job. This is the work happening around it, in the two places we usually start.

3PL and fulfillment

The WMS already runs receiving, inventory, and shipping. The work that is left needs a person to interpret a request, coordinate the change, investigate what went wrong, move information between systems, communicate, and keep the process moving.

  • Client changes

    A client emails a change to a SKU, an order, a routing rule, or a special handling requirement. AI employees read it, work out what it means operationally, update the right systems, and confirm it back.

  • Exception resolution

    Short receipts, damaged inventory, failed shipments, and address problems are picked up as they happen, investigated against the record, resolved where the answer is clear, and escalated with context where it is not.

  • Client onboarding

    New client requirements arrive as email, spreadsheets, and calls. AI employees structure them, chase what is missing, set up what can be set up, and keep the launch moving without a coordinator running it by hand.

Freight, brokerage, carriers, and transportation

The same pattern around the TMS and the transportation workflow, where most of the manual work is reading a message, deciding what changed, and telling the right systems and people about it.

  • Incoming changes

    Orders, appointments, rates, and requirements arrive as email, PDFs, portals, and phone calls. AI employees read them, structure them, and update the TMS instead of a coordinator retyping them.

  • Exception resolution

    Delays, detention, missed appointments, and paperwork problems are caught as they happen, worked where they can be, and handed to a person with the full picture when judgment is needed.

  • Customer and carrier coordination

    Status, updates, and the back-and-forth of keeping freight moving are handled continuously, so people are not spending their day making the same calls and sending the same updates.

The WMS does its job. The TMS does its job. Code Quarry handles the operational work happening around them.

What changes

A better business feels different.

The benefit is not more technology. It is what your people and your business can do when routine work stops consuming the day.

  1. 01

    Save operational cost

    Your back office stops re-keying orders, chasing documents, and sending the same updates by hand.

  2. 02

    Give valuable people their time back

    Coordinators spend their time on the exceptions, the relationships, and the accounts that need them.

  3. 03

    Catch revenue slipping through the cracks

    Detention, accessorials, and billing-ready work are less likely to get written off or stall between the load and the invoice.

How we work

Three phases, from first look to a running AI employee.

  1. 1We prove what is worth doing together.
  2. 2We build it with you.
  3. 3We operate and improve it for you.

Nobody is asked to buy a proposal for work they have not seen quantified, and nobody is left running the AI on their own after launch.

  1. 1

    Prove what is worth doing

    Feasibility and business case

    We come in and watch how the work actually happens. Together, we identify what an AI employee can realistically take over, where a person still needs to be involved, and what the opportunity is worth.

    1. Step 1Watch the work

      See how the process actually happens. The people closest to the work share their screens and walk through the real systems, handoffs, documents, decisions, exceptions, and workarounds.

      You getA clear picture of where people are carrying work around and between the systems you already have.

    2. Step 2Find the work

      Identify the costly operational work that AI employees and automation can take over.

      You getA short list of the work worth taking off your people, in your own vocabulary.

    3. Step 3Do the math

      Quantify the current state: who, times minutes, times frequency. Also delays, error risk, capacity limits, missed revenue, cash trapped, and what happens when nobody catches an exception.

      You getThe cost of the work as it runs now, in numbers you can check against your own operation.

    Before we recommend a build, we confirm the work is technically and operationally feasible, and we put a number on the cost, time, capacity, or revenue opportunity.

  2. 2

    We build it with you

    Collaborative build

    Code Quarry owns the design and build, while working closely with your team to make sure the AI employees fit your operation. Your people help define the rules, exceptions, approvals, and human boundaries. We test the work together before launch.

    1. Step 4Build the employee

      Design what the AI employee will understand, decide, do, communicate, monitor, and escalate. Keep deterministic rules deterministic. Keep people responsible for judgment, approval, relationships, and high-risk exceptions. Then build it around the systems already in place.

      You getWorking AI employees, integrated with your existing tools and tested against criteria you agreed to up front.

    Code Quarry

    • Design and build the AI employees
    • Handle the technical work, integrations, and testing
    • Fit the result to how the business actually operates

    Your team

    • Share how the work really happens
    • Define the rules, exceptions, and approvals
    • Decide where a person stays involved
  3. 3

    We operate and improve it for you

    Managed AI partnership

    After launch, Code Quarry stays responsible for watching, validating, improving, and proving the performance of your AI employees. You stay focused on the business. We make sure the AI employees keep doing the job they were built to do.

    Continuous monitoring, weekly validation, tested changes, monthly improvement, and a written report that proves the value.

    See what the managed partnership includes

Your first step is a conversation.

Let's talk about the work.

A practical conversation about where your people are doing manual work today, and whether AI employees can take it over.