Commercial property work orders and vendor email, 15 management firms
Summary
Work orders and vendor correspondence from 15 US commercial property management firms running office, industrial flex and retail portfolios. Each work order carries the tenant request, building engineer notes, vendor dispatch, labor time and completion, so a model sees a building problem from first report to close. Some engineer notes are in Spanish. Residential and multifamily properties, access-control and security incident records and tenant employees' names and phone numbers are left out.
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 pricingAt a glance
- Planned scope. Volume, sources and timing are confirmed in writing before you sign.
- Records
- 8Mwork orders and vendor emails
- Size
- 14.1 GB
- Tokens, estimated
- 1.6B
- Years
- 2015 to 2026
- Firms
- 15
- Owner profile
- 15 US commercial property management firms, 25 to 300 staff each, Texas, the Southeast and the Mountain West
- Industry
- Real estate
- Data type
- Field operations
- Headcount
- 25 to 300 staff per firm
- Region
- United States (Texas, Southeast, Mountain West)
- Languages
- English, Spanish
- Formats
- JSONL
- Updated
Sources
| System | Kind | Records |
|---|---|---|
| Yardi Voyager | Field operations | 2.91M work orders |
| Building Engines | Field operations | 1.42M work orders |
| Microsoft 365 mail | 3.69M messages |
Good for
- training agents to triage tenant requests and dispatch building engineers or vendors
- predicting repeat equipment failures by building age and season
- evaluating extraction of root cause and corrective action from technician notes
- modeling vendor scope, scheduling and follow-up in commercial buildings
Fields
| Field | Type | Description |
|---|---|---|
| work_order_id | string | Stable work order id |
| manager_code | string | Code of the contributing firm |
| property_ref | string | Property code, stable across records |
| property_type | enum | office, industrial_flex, retail or mixed_use |
| category | enum | hvac, electrical, plumbing, elevator, roofing, janitorial, life_safety or general |
| priority | enum | emergency, urgent, routine or preventive |
| requested_at | timestamp | Request time in UTC |
| completed_at | timestamp | Completion time in UTC |
| requester_role | enum | tenant, property_manager, engineer or vendor |
| notes | array<string> | Engineer, vendor and tenant notes in order, with local times |
| labor_minutes | int | Recorded labor time |
| vendor_ref | string | Coded vendor, empty when the work was done in house |
Example record
{
"work_order_id": "PM08-WO-2291784",
"manager_code": "PM-08",
"property_ref": "[SITE_14]",
"property_type": "office",
"category": "hvac",
"priority": "urgent",
"requested_at": "2025-07-15T19:02:00Z",
"completed_at": "2025-07-15T22:47:00Z",
"requester_role": "tenant",
"notes": [
"15:02 Tenant [COMPANY_31] reports suite 410 conference rooms at 79F before a 4pm client meeting",
"15:20 Engineer on site. VAV 4-12 damper stuck at 30 percent, actuator not responding to BAS command",
"16:05 Se cambió el actuador de la caja VAV 4-12 con uno del almacén, flujo mínimo y máximo recalibrado según el reporte TAB",
"18:40 Space at 72F, setpoint restored, confirmed with [PERSON_18]"
],
"labor_minutes": 145,
"vendor_ref": ""
}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.