Logistics
Every customer has their own “on time.”
Your WMS counts it one way. Your TMS counts it another. The carrier feed has a third answer, and the customer's scorecard uses none of them. We map every definition to the fields that produce it, build the platform under it, and put AI to work on numbers you can defend in any QBR.
For 3PL and 4PL providers. Built by a team that has run logistics data, not just read about it.
A plant argues with itself. You argue with your customers.
Every contract carries its own definition of on time, in full, dwell, and damage. Your account teams keep them all straight, customer by customer, mostly by hand. That is real expertise. It also gets harder with every contract you sign.
On time.
Pickup window, delivery appointment, first attempt, or proof of delivery? One shipment, four timestamps, four answers.
In full.
Ordered, allocated, picked, or received without exception? Each customer counts a short ship differently.
Chargebacks.
When their scorecard and yours disagree, theirs wins. You pay for a definition you never agreed to.
Cost to serve.
Accessorials, detention, and rework live in billing, the TMS, and email. Without one definition, you can't see which accounts actually make money.
The model is right about the data and wrong about the business.
A 4PL runs on other people's systems: several WMS instances, a TMS, carrier EDI and API feeds, and each customer's ERP. The same field name means something different in each one. Point an agent at all of it and it can't tell that “delivered” in one feed is “POD received” in another. It will still answer you, confidently.
AI inherits every definition you never agreed on. In logistics, you inherit your customers' too.
Many definitions, one map
We don't force your customers onto one definition. That's not your business.
We build a lexicon: each customer's definition of on time, in full, and dwell, mapped to the exact fields in your systems that produce it. Two definitions can live side by side when they serve different customers. One name can't carry two meanings.
- Report every customer on their own terms
- See your own network on yours
- Catch a scorecard miss before the customer does
- Give AI a map instead of a guess
Start with your people. Scale one value stream. Connect the network.
01
Start: your people
Get in a Flow working sessions. Account managers, dispatchers, and analysts set up their AI tools as standard work: QBR prep, rate and contract summaries, exception emails drafted for a person to approve before they go.
02
Scale: one value stream
Start with the Definition Audit: about three weeks, fixed fee. We compare your reports, customer scorecards, and SQL, find the biggest gap, and put a dollar figure on it. Then we take one value stream, usually order to delivery. We land data from your WMS, TMS, and carrier feeds, ratify definitions customer by customer, and put one agent to work. A typical first agent: flag shipments drifting from a customer's own definition of on time while there's still time to act.
03
Connect: the network
Billing, carrier performance, cost to serve. Each new stream reuses the data already landed. We never charge twice to bring in the same data.
Built on what you already run.
Source systems.
WMS, TMS, carrier EDI and API feeds, telematics, customer portals, and ERP. Whatever mix you've grown into.
Platform.
Postgres or SQL Server today is fine. Planning a move to Snowflake or Databricks? Settle the definitions first and the move carries clean meaning instead of copying the disagreement into a more expensive place.
Reporting.
Power BI, Metabase, or what you run today. The definitions and the semantic model are the product. The dashboard is a swap.
What you own when we leave.
- A customer-by-customer definition map, versioned, stored in your database
- Every internal metric with one owner and one written definition
- A semantic model your reports and your agents both read
- Pipelines running in your environment
- One agent in production in your first value stream
- A team that knows how to run it. We don't host it, and you're not renting it from us.
Your data, and your customers' data, stays in your environment. Always.
ISO/IEC 42001
This is not a methodology. It's a control.
Every AI use case we deliver is documented against ISO/IEC 42001. When a customer asks how you know a number is right, you can show them the definition, the owner, and the history.
Questions
What logistics leaders ask first
You get their version. This gives you yours, mapped to theirs, so you can see a miss coming and argue a chargeback with evidence.
No. We work with the systems you run and the feeds you already get.
It's the best time. Moving data you haven't defined just moves the disagreement.
One half-day working session per value stream to ratify definitions. Most of the rest happens through interview agents that ask owners questions on their own time, not in another meeting.
Definitions are kept customer by customer, and nothing leaves your environment.
We build it. The Audit makes sure the build is worth doing.
Bring us one customer's scorecard.
Thirty minutes. Put one customer's scorecard next to your own numbers, and we'll show you where they split and what it's costing.