THE #1 AI-ENHANCED BLUE-COLLAR JOB DATABASE · API + BULK EXPORTS

The blue-collar job market,ready to query and export.

Turn fragmented employer vacancies into normalized, source-linked job data. AI assists with occupation classification and selected field enrichment; it never generates the underlying listings. Evaluate the data through API access or bulk exports.

Get sample records See how it connects

AI-assisted classification CSV + JSON samples Field dictionary

FITS YOUR STACK

Direct API Apify planned n8n via HTTP Zapier via webhook

PRODUCT STORYFrom public pages to usable job data

PUBLIC EMPLOYER SITESFRAGMENTED

Sample Fabrication18m ago

CNC machinistCleveland, US

Northline Energy27m ago

Industrial electricianCalgary, CA

Harbor Cooling41m ago

HVAC technicianTampa, US

Transit Works1h ago

Diesel mechanicBrisbane, AU

Alloy Systems2h ago

Production welderBirmingham, UK

Thousands of listings. Different layouts. No shared schema.

API RESPONSE200 OK

GET/v1/jobs?occupation=electrician&status=active

{
  "data": [
    {
      "job_id": "bcjd_86a1",
      "occupation": "Industrial electrician",
      "location": { "city": "Calgary", "country": "CA" },
      "status": "active",
      "last_seen": "2026-08-08",
      "source_url": "https://careers.example/job/184"
    }
  ],
  "next_cursor": "sample_02"
}

One response shape for products, analysis and automation.

01 / 05Across the webPublic employer job pages

24 SEC LOOP

01SOURCE-DIRECT

Employer-controlled career pages

02EXPORT-READY

CSV, JSON and API-shaped records

03TRACEABLE

Source and observation context

04WORKFLOW-READY

Standard HTTP and structured data

PLANNED DELIVERY PATHS

Job data that lands where your team already works.

Standard HTTP and structured JSON make the dataset suitable for developer tools, automation platforms and your own data stack. Native templates are a planned product layer.

Tell us what you use

Apify

Actor or dataset adapter

PLANNED

n8n

HTTP Request workflow

WORKFLOW

Zapier

Webhooks or custom request

WORKFLOW

Direct API

REST + JSON client

CORE

BLUE COLLAR JOB DATAHTTPS / JSON

APIFYN8NZAPIERYOUR APP

Early access is scoped directly with buyers. Native templates and vendor partnerships are not yet available.

01 / 11THE DATA GAP

HIDDEN IN PLAIN SIGHT

One job page shows an opening.Connected records show demand.

Collection is only the beginning. Useful job postings data needs a shared structure, repeated observation and clear provenance.

01TITLE ≠ ROLE

Every source speaks differently.

Titles, places, work types and dates arrive in thousands of different shapes.

02LAST SEEN —

Listings quietly disappear.

Repeated observation is what reveals whether a listing opened, changed or left the source.

03SOURCE / MANY

Employers stay fragmented.

Public hiring demand is scattered across individual career sites and local vacancy pages.

04RECORD → SIGNAL

The market remains invisible.

One job page shows an opening. Connected records show the shape of demand.

02 / 11THE VISIBILITY LAYER

ONE RECORD / FIVE STATES

The web does not share a schema.The dataset does.

Follow one vacancy from an isolated source page into a traceable record that can join the wider market view. Select a stage to see what changes and what is preserved.

SCHEMA / V1STEP 03 / 05

CURRENT RECORD

Electrician

OCCUPATIONElectrical trades

CHANGED

CITYRotterdam

NORMALIZED

WORK TYPEFull-time

NORMALIZED

PROVENANCE RETAINED

03 / 11DELIVERY MODES

ONE LAYER / THREE PRODUCTS

One dataset. Three ways to work with it.

Use the same normalized layer through a job posting API, as bulk job data or as evidence for labor-market reporting.

QUERY

Job data API

Filter normalized records by market, occupation, employer, place and observed freshness.

Inspect sample response

ANALYZE

Bulk datasets

Bring analysis-ready job records into a warehouse, model, research project or data product.

See the sample package

EXPLAIN

Market reports

Turn the same records into evidence-led views of places, occupations and employers.

Preview report formats

04 / 11DATASET ANATOMY

FIELDS WITH A MEMORY

A record should explain where it came from.

Structured job data is more useful when preserved source values, normalized fields and observation states remain visibly distinct.

job_idstringGenerated

Stable normalized record identifier

titlestringPreserved

Title retained from the source listing

companystringPreserved

Employer attached to the original source

citystringNormalized

Comparable city and geography value

occupationstringClassified

Consistent occupation family

first_seendate-timeObserved

First successful source observation

last_seendate-timeObserved

Most recent successful observation

sourceenumTraceable

Source type with lineage retained

PRESERVED NORMALIZED OBSERVEDRequest full field dictionary

COVERAGE TRUTH LAYERSTATUS / PUBLIC PLAN

Current launch market In development Long-term vision

05 / 11COVERAGE + FRESHNESS

THE EDGES ARE PART OF THE PRODUCT

See what is measured—and what is not.

Trust begins with scope. Every commercial snapshot should state the market, source definition, observation date, freshness rules and known exclusions.

Review current coverage

Netherlands

Current launch market

CURRENT

United States

Coverage build-out

IN DEVELOPMENT

Global layer

Long-term platform vision

PLANNED

06 / 11FROM RECORD TO DECISION

BUYER OUTCOMES

One dataset. Different questions.

The same record layer can support workforce analytics, recruitment products, hiring signals and original market research.

Workforce analytics

Where is skilled demand changing?

API + BULK

Recruitment products

Which current records should power a search, alert or workflow?

API

Hiring signals

Which employers changed their hiring activity?

API + EXPORT

Market research

How do occupations, places and employers compare?

BULK + REPORTS

07 / 11MARKET REPORTS

DATA AS PUBLIC EVIDENCE

The same layer can explain a labor market.

Original reports will turn verified job market data into readable city and occupation stories. United States reports publish only after their coverage supports meaningful, unique analysis.

REPORT FORMAT / 001PUBLICATION STANDARD

FUTURE UNITED STATES SERIES

New York job market

Publish after verified source coverage

Houston job market

Publishes after verified coverage

US / PLANNED

Seattle job market

Publishes after verified coverage

US / PLANNED

Chicago job market

Publishes after verified coverage

US / PLANNED

No thin city pages: each report needs a defined snapshot, unique findings, methodology and limitations.

Review the publication standard

08 / 11METHODOLOGY

A VISIBLE PROVENANCE LEDGER

The method travels with the record.

A credible dataset explains collection, transformation and limitations alongside the output—not in a footnote after the sale.

Read the methodology

01Source

Begin with publicly available company career sites and employer-controlled vacancy pages.

02Observe

Retain the source route and observation times needed to describe provenance and lifecycle.

03Normalize

Turn inconsistent titles, locations and attributes into comparable fields while preserving source values.

04Track

Use repeated observations to distinguish first seen, last seen, changed and no longer observed states.

05Disclose

Publish market scope, snapshot date, definitions and known limitations alongside the data.

09 / 11SAMPLE PACKAGE

START WITH THE RECORDS

Know what you are evaluating.

Request representative records with a field dictionary, source example and dated coverage note. We'll scope the sample to the market and workflow you're evaluating.

Inspect sample data

Normalized records

Representative sample records

Field dictionary

Definitions + lineage

Provenance example

Source + observation

Coverage note

Scope + limitations

10 / 11FAQ

DATA BUYER QUESTIONS

What to know before you evaluate the data.

Evaluate the records against clear coverage, field and delivery definitions before you buy.

01What is blue-collar job data?

Structured records describing skilled-trade, frontline, field-service, logistics, manufacturing and related vacancies. The product turns many fragmented sources into a consistent format for analysis and software products.

02Where do the job listings come from?

The collection model is built around publicly available company career sites and employer-controlled vacancy pages. Published samples retain source and observation context.

03Is this a job posting API or a tool for publishing jobs?

It supplies job-posting data for reading and analysis. It is not an API for sending vacancies to job boards. The planned delivery modes are queryable API access and bulk datasets.

04Which markets are covered?

The Netherlands is the current launch market. United States coverage is in development. Public coverage statements will always include a date and scope definition.

05Can I inspect the fields before buying?

Yes. The evaluation package is designed to include normalized sample records, a field dictionary, a provenance example and a current coverage note.

06How are duplicate and inactive records handled?

The methodology retains source identity and repeated observations. Exact deduplication and lifecycle definitions are documented with each commercial dataset so the rules match the market and delivery.

11 / 11NEXT STEP

EVALUATE THE LAYER

Start with the records, not the sales pitch.

Tell us the market, occupations and workflow you want to evaluate. We will use that context to shape the sample package and integration path.

Get sample records Inspect sample fields

SAMPLE PACKAGE / SCOPED TO YOU● REQUEST OPEN

MARKET: Netherlands
CONTENT: Records + fields + provenance
DELIVERY: API or bulk evaluation
STATUS: Market + use case required

Open sample request