Mechanical contractor with construction and service divisions, 2015 to 2026

Summary

The working archive of one US mechanical contractor that builds and then services HVAC and plumbing systems in commercial buildings. It joins project records, service work orders, estimating files, mail and public team channels, so the same building appears first as a bid, then as an install, then as a maintenance customer. People and buildings carry the same placeholder in every system, and HR, payroll and legal material is excluded at collection.

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
25.6Memails, chat messages, project records, work orders and documents
Size
73.6 GB
Tokens, estimated
8.3B
Years
2015 to 2026
Firms
1
Owner profile
One US mechanical contractor, 300 to 500 staff, construction and service divisions
Industry
Construction
Data type
Company operations archive
Headcount
300 to 500 staff
Region
United States
Languages
English
Formats
JSONL, Parquet
Updated

Sources

SystemKindRecords
Microsoft 365 mailEmail21.7M messages
Slack public channelsTeam chat2.3M messages
ProcoreProjects and wiki382K RFIs, submittals, change events and minutes
ServiceTitan work orders (2019 onward)Field operations612K work orders
Shared drives (estimates, schedules, commissioning, closeout)Shared files560K documents

Good for

  • evaluating long-context reasoning that follows one building from bid to install to service
  • training agents that draft submittal transmittals and track reviewer comments
  • fine-tuning models to answer field questions from internal channel history
  • linking service failures back to installation decisions for root-cause analysis

Fields

FieldTypeDescription
record_idstringUnique record id
systemenummail, chat, project_mgmt, field_service or drive
building_idstringPlaceholder for the building, shared across all systems
project_idstringPlaceholder for the construction job, where one applies
created_attimestampCreation time with the original UTC offset
author_roleenumRole of the author, such as project_manager, estimator, foreman, service_manager or technician
subjectstringSubject, channel topic or record title
textstringDe-identified body text
linked_recordsarray<string>Records in other systems about the same building or job
folder_pathstringOriginal folder, channel or module path

Example record

{
  "record_id": "MC1-MAIL-14420917",
  "system": "mail",
  "building_id": "[SITE_204]",
  "project_id": "[PROJECT_1187]",
  "created_at": "2022-01-11T07:36:00-06:00",
  "author_role": "service_manager",
  "subject": "RE: [SITE_204] RTU-3 heat exchanger, warranty or not",
  "text": "Pulled the closeout binder from the 2019 job. RTU-3 started up 9/2019, so the 5 yr heat exchanger warranty is still good, parts only. Labor is on us per the service agreement. [PERSON_31] please open the claim with the rep and attach the startup sheet. Tech read 140 ppm CO in the flue at high fire, unit stays locked out until we swap it.",
  "linked_records": [
    "MC1-PM-SUB-0091822",
    "MC1-FS-WO-0420733"
  ],
  "folder_path": "Inbox/Service/Warranty"
}
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-23358

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