Freight brokerage TMS loads with carrier sales and tracking email, 12 firms

Summary

Load records from 12 asset-light truckload brokerages, each joined to the carrier sales, rate confirmation and track-and-trace email around it. Covers dry van, reefer and flatbed lanes with check calls, detention and TONU disputes, and shortage and damage claims. Useful for training agents that book, cover and track loads, and for evaluating reasoning about accessorials and service failures. Shipper, carrier and driver identities are replaced, MC and DOT numbers removed and all rates masked.

Collected to order. We collect it from US companies for your order. Scope, volume and timing are confirmed in writing before you sign.

Pricing on request

Request scope and pricing

At a glance

  • Planned scope. Volume, sources and timing are confirmed in writing before you sign.
Records
18.7Mloads, emails and channel messages
Size
46.2 GB
Tokens, estimated
4.9B
Years
2015 to 2026
Firms
12
Owner profile
12 US asset-light freight brokerages, 6 to 70 staff each, Southeast, Midwest and Texas
Industry
Logistics and freight
Data type
Logistics and supply chain
Headcount
6 to 70 staff per firm
Region
United States (Southeast, Midwest, Texas)
Languages
English, Spanish
Formats
JSONL, Parquet
Updated

Sources

SystemKindRecords
Brokerage TMSOrders and point of sale2.9M loads
Google Workspace mailEmail14.2M messages
Slack public channelsTeam chat1.6M messages

Good for

  • training agents to cover loads by matching carriers to lanes, confirming terms and dispatching
  • automating check calls and exception updates from carrier email and tracking notes
  • evaluating reasoning on detention, layover and TONU disputes against rate confirmation terms
  • classifying and drafting cargo claims for shortage and damage

Fields

FieldTypeDescription
load_idstringLoad number in the TMS
firm_codestringPool member code
modeenumdry van, reefer, flatbed or power only
originstringOrigin city placeholder and state
destinationstringDestination city placeholder and state
pickup_attimestampPickup appointment
delivery_attimestampDelivery appointment
carrier_codestringPlaceholder for the carrier
statusenumbooked, dispatched, in transit, delivered, canceled or TONU
check_callsarray<string>Tracking updates in order
accessorialsarray<string>Accessorials claimed and their outcome, amounts masked
email_thread_idsarray<string>Linked carrier and shipper threads

Example record

{
  "load_id": "LD-2025-311904",
  "firm_code": "FRT-09",
  "mode": "reefer",
  "origin": "[CITY_14], GA",
  "destination": "[CITY_3], OH",
  "pickup_at": "2025-06-17T06:00:00-04:00",
  "delivery_at": "2025-06-18T22:30:00-04:00",
  "carrier_code": "[COMPANY_206]",
  "status": "delivered",
  "check_calls": [
    "06/17 05:40 at shipper, checked in, door 12",
    "06/17 09:55 loaded, reefer set 38F continuous, seal on BOL",
    "06/18 13:10 driver on 10 hr break near [CITY_8], ETA 22:00",
    "06/18 22:41 delivered, 2 cases crushed, noted on BOL"
  ],
  "accessorials": [
    "detention 2 hr at shipper, approved with in and out times"
  ],
  "email_thread_ids": [
    "TH-881204",
    "TH-881377"
  ]
}
One record, de-identified. Placeholders such as [PERSON_12] and [COMPANY_4] stay the same across the whole dataset, so threads still read correctly.

Licenses available

  • Exclusive

    One buyer. Nobody else can license it during the exclusive term, usually 2 years.

  • Non-exclusive

    Licensed to more than one buyer.

  • First look

    One buyer gets 2 to 4 weeks to make an offer before anyone else sees the dataset.

What ships with it

  • Datasheet: what it is, what it is good for, verified size, sources, years, format and limits.
  • Provenance file: the owner shown by code, staff notice and consent status, exclusions, mapped to the EU AI Act Article 53 training-data summary and California AB 2013.
  • Manifest with a hash for every file.
  • QC report and de-identification report.
  • Your own copy, with unique canary records.

How it is de-identified

Default exclusions removed, files flattened to text, identifiers found in three layers and replaced with consistent placeholders, and the result measured against a 99% bar for each identifier type in each source.

The full method

Request scope and pricing

We confirm scope, volume and timing in writing before you sign. Samples go out under evaluation terms after a short buyer check, once the first records are in.

Dataset: NK-34529

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