Company Tech Stack Scraper — BuiltWith Alternative

What this Actor scrapes

Three ATS platforms, one unified schema:

1. Greenhouse — boards-api.greenhouse.io/v1/boards/{token}/jobs?content=true 2. Lever — api.lever.co/v0/postings/{token} 3. Ashby — api.ashbyhq.com/posting-api/job-board/{token} (token is case-sensitive — Ramp, not ramp)

What we handle for you

• Three ATSs, one schema — Greenhouse, Lever, and Ashby normalised to an identical row shape.
• Curated tech vocabulary — ~110 canonical names spanning languages (Python, Go, Rust), frameworks (Django, React, FastAPI), databases (Postgres, MongoDB, Redis, Snowflake), cloud (AWS, GCP, Azure, Vercel), infra (Kubernetes, Terraform, Docker), CI/CD, observability, and ML/data tools.
• Per-company fault isolation — one bad token (404 from Lever, typo on Ashby) does not abort the run; the other companies still produce data.
• Pydantic v2 validation — every input and every output row is model-validated before landing in the dataset.
• Filter knobs — maxJobsPerCompany cap and minTechsDetected floor let you drop generic non-engineering postings.
• Exponential backoff — 408 / 429 / 503 retries with Retry-After honoured; up to 5 attempts per request.
• Deterministic detection — regex + vocabulary, not LLM. High precision, zero hallucinated tools.

Use cases

• B2B sales qualification — enrich every Salesforce or HubSpot account with the company's live back-end stack: "they hire Django + Postgres + AWS" tells you whether to pitch your Postgres-tuning SaaS.
• Recruiter sourcing — pull every senior backend role from your target accounts and filter by detected_techs to find teams that match your candidate's stack.
• Competitive intelligence — track which competitors are hiring for Kubernetes or Snowflake and infer their roadmap before it's announced.
• CRM enrichment — replace TheirStack / BuiltWith / Wappalyzer subscriptions for the segment of buyers who publish their stack in job descriptions anyway.
• Investment research — map private-company tech footprint over time without a Crunchbase Pro seat.
• Open-source stack maps — feed a public page that ranks the most-hired-for technologies among YC-backed startups.

Input

Paste this into the Apify Console, or send it as the run input over the API. Proxy settings are on by default; you rarely need to touch them.

{
  "companies": [
    {
      "companyToken": "airtable",
      "atsType": "greenhouse"
    },
    {
      "companyToken": "Ramp",
      "atsType": "ashby"
    }
  ],
  "minTechsDetected": 0,
  "useProxy": false
}

Output

One row per result, schema-validated before it is written. Export JSON, CSV, Excel or XML from the run, or read it over the API.

atscompany_tokenjob_idtitlelocationdepartmenturldescription_textdetected_techsposted_atscraped_at

{
  "ats": "greenhouse",
  "company_token": "airtable",
  "job_id": "4812345",
  "title": "Senior Backend Engineer",
  "location": "Remote",
  "department": "Engineering",
  "url": "https://boards.greenhouse.io/airtable/jobs/4812345",
  "description_text": "We use Python, Django, PostgreSQL, and AWS...",
  "detected_techs": [
    "AWS",
    "Django",
    "Postgres",
    "Python"
  ],
  "posted_at": "2026-05-01T09:00:00Z",
  "scraped_at": "2026-06-01T12:00:00Z"
}

Pricing

You pay only for results that land. Cap any run with maxTotalChargeUsd. See pricing & billing for worked examples.

Limitations

• Tech detection is regex-based, not LLM-based — it is deterministic and high-precision, but will miss tools not in the curated ~110-name vocabulary. Submit a feedback request to add more terms.
• ~85% recall — job descriptions that omit or abbreviate tool names will not surface every dependency in a company's stack. This is an inherent limit of job-description parsing, not an Actor bug.
• Ashby tokens are case-sensitive — Ramp works; ramp returns zero jobs. Double-check the exact token from the company's Ashby board URL.
• Greenhouse double-encoding — Greenhouse wraps its content field in double HTML-encoding (<div> for <div>). The parser unescapes twice before stripping tags; unusual encoding in edge-case boards may still slip through.
• Lever descriptionPlain gaps — Lever sometimes omits the "Requirements" bullet list from descriptionPlain. The parser concatenates every lists[].content chunk to recover skills listed there; however, lists in non-standard formats may be missed.
• Default dataset retention — Apify FREE-tier default storage retains datasets for 7 days. Use Actor.open_dataset(name="…") or export immediately if you need to outlive that window.
• No personal-data extraction — this Actor reads public job posts and company-aggregated tech signals only. It does not extract candidate data or applicant details from any ATS.