Company Discovery List Builder Market In Companies Out

🧭 What can Company Discovery List Builder do?

Give it a market definition and it returns the companies in that market, one flat row each. Every other company data tool takes a company and tells you something about it. This one builds the list in the first place, with no paid database behind it.

Two ways to define a market. Hiring: job role keywords, optionally a location, and you get companies with that role open right now. Filings: a phrase, and you get US SEC filers whose filings contain it.

📦 What you get	⚙️ Features and integrations
🏢 Companies, not enrichment, one flat row each 🧾 25 fields, always all 25, null never missing 📏 universe_size on every row, your denominator 🔗 evidence_url, the posting or filing it came from	🔍 Hiring mode over live Greenhouse and Ashby boards 🏛️ Filings mode over SEC EDGAR full text search 🧊 30 day universe cache, live job data on top ⬇️ Export to JSON, CSV, Excel, HTML or XML

Bought by outbound teams building a target list from scratch, and by anyone who wants a market defined by what companies are doing rather than by a vendor's static database.

🚫 This is not a company database and it does not cover every company. It enumerates a named, published universe and tells you how big it was. If you want fields about companies you already have, use Company Firmographic Enricher.

💡 Why use Company Discovery List Builder?

If you want	Read these fields
The company list itself	company_name, company_domain
To know why a company is on your list	match_reason, evidence_url
To judge the list's coverage	universe_size, universe_source, universe_built_at
Hiring intensity as a qualifier	open_jobs_count, matched_job_count, matched_job_title
Geography	matched_job_location, locations_count
The public filer identity	ticker, cik, filing_form
To tell empty from broken	fetch_status, is_summary_row

📏 Read universe_size before you read anything else

universe_size and universe_source ship on every single row, and they are the two most useful fields in the output.

If the actor returns 40 companies, 40 on its own means nothing. 40 out of 9,266 candidates from three named Common Crawl collections is a number you can act on. A list builder that hides its denominator is asking you to trust it, and you should not have to.

Measured on build 0.0.3: universe_size 9,266 cold and 9,266 warm from the same query, with universe_source naming common_crawl:CC-MAIN-2026-30+CC-MAIN-2026-25+CC-MAIN-2026-21.

A company missing from your results is missing because it was not in that pool or did not match your filter. It is not a statement that the company is not in your market.

📋 What data can Company Discovery List Builder extract?

25 fields, always all 25. A value that is not available comes back null, never missing.

Field	What it holds
company_name	The name as the source publishes it
company_domain	Resolved website, when domain resolution is on and confident
domain_status	resolved, low_confidence, not_found, not_attempted, search_failed
domain_confidence	0 to 100
match_reason	Why this company is in your list, in plain words
mode	hiring or filings
ats_provider, ats_slug, careers_url	Which board, whose, and where
open_jobs_count	Live open roles on the board
matched_job_count, matched_job_title	How many matched your keywords, and the first one
matched_job_location, locations_count	Its location string, and how many distinct ones the board carries
ticker, cik, filing_form	Filings mode only
evidence_url	The job posting or SEC filing this row came from
universe_source, universe_size, universe_built_at	Where candidates came from, how many, and when
fetch_status, fetch_error	ok, partial, universe_error, no_results
is_summary_row	True only on the fallback row when a run finds nothing
run_date	When the run happened

⚠️ universe_size is null, never 0, when the pool could not be loaded. Zero would read as a real measurement of an empty market. A universe_error row means there was no honest denominator to report, which is a different thing from a market with nobody in it.

🛠️ How to build a company list from a market definition

1. Open the Input tab and pick a mode, hiring or filings.
2. For hiring, put comma separated job titles in role_keywords, and optionally a city or region in location_contains.
3. For filings, put the phrase in filing_phrase and pick filing_forms.
4. Set max_companies to cap the list.
5. Click Start, then read universe_size before you read the rows.

🧪 Using it in Clay

Run it once to build the list, then export and import the rows as a Clay table. This actor creates rows rather than enriching them, so it is the step before the rest of the suite, not a column inside it.

Turn resolve_domains off for the first pass. It is on by default, looking up each company's website, and a cleaner company name list is easier to resolve deliberately afterward.

🎯 How role matching works

Keywords are comma separated and matched as whole words against live job titles. Lowercased, no stemming, no fuzzy distance, no AI guessing.

account executive matches "Account Executive, Expansion" and "Enterprise Account Executive". It does not match "Executive Assistant" or "Accounts Executive".

That is deliberate. You can predict exactly what it will do, which matters more on a list you are going to email than a few extra rows you cannot audit. Leave the keywords empty to match any role.

💵 How much does it cost to build a company list?

You are billed per company returned, not per company examined. A query that matches nothing costs one run, not thousands of charges.

Plan	Price per company found
Free	$0.004
Bronze	$0.0038
Silver	$0.0036
Gold	$0.0034

There is also an Actor start event at $0.00005, charged once per run per GB of memory.

💳 The summary row is never billed. When a query legitimately matches nothing, the run emits one row with is_summary_row: true so you can see the query ran against the whole pool. That row carries no charge, and neither does a universe_error row.

⌨️ Input

Everything is on the Input tab. The options worth explaining:

Field	Type	Default	What it does
mode	string	hiring	hiring or filings.
role_keywords	string	empty	Comma separated job titles. Empty matches any role.
filing_phrase	string	empty	Filings mode: the phrase to find in SEC filings.
filing_forms	string	10-K	Filings mode: which forms to search.
location_contains	string	empty	Plain substring match on the job's location string.
min_open_jobs	string	1	Skip boards with fewer open roles than this.
max_companies	string	100	Ceiling on the returned list.
resolve_domains	boolean	true	Try to resolve each company to a website.
refresh_universe	boolean	false	Rebuild the candidate pool instead of using the cache.

📤 Output

One flat row per company, exportable as JSON, CSV, Excel, HTML or XML.

{
  "company_name": "7shifts",
  "match_reason": "hiring: Account Executive, Expansion (Toronto, ON) and 3 more matching roles",
  "mode": "hiring",
  "ats_provider": "greenhouse",
  "ats_slug": "7shifts",
  "careers_url": "https://job-boards.greenhouse.io/7shifts",
  "open_jobs_count": 15,
  "matched_job_count": 4,
  "matched_job_title": "Account Executive, Expansion",
  "matched_job_location": "Toronto, ON",
  "locations_count": 6,
  "universe_source": "common_crawl:CC-MAIN-2026-30+CC-MAIN-2026-25+CC-MAIN-2026-21",
  "universe_size": 9266,
  "fetch_status": "ok",
  "is_summary_row": false
}

💡 Tips

• Read universe_size first, every time. It is the difference between a list and a number.
• resolve_domains is on by default and looks up each company's website; turn it off to start. Get the company list right, then resolve.
• location_contains is a substring match on free text. Try the shortest distinctive fragment, London rather than London, UK.
• Use min_open_jobs to drop companies with a single stale posting.
• Run it monthly. The universe refreshes about monthly and the job data underneath is live.

⚠️ Known limits

Read these before you buy a run. A list builder that hides its coverage bias is worse than one that returns fewer companies.

The hiring mode only sees companies with a public Greenhouse or Ashby job board. That is about 9,266 companies in the current index, skewed heavily toward venture-backed technology companies in the US and Europe. If your market is manufacturing, professional services, healthcare providers, or anyone on Workday, SuccessFactors, iCIMS or a custom careers page, this mode will mostly miss them. That is a coverage limit, not a bug.

Lever boards are not covered at all, and cannot be. Lever's robots.txt tells Common Crawl's crawler not to index the site, so no Lever board pages exist in the index to enumerate. The only Lever records in the crawl are robots.txt itself. The actor still knows how to read a Lever board and will use it the day that changes, but today Lever coverage through this route is zero. Unioning older crawls does not help, because the exclusion applies to all of them.

The universe refreshes about monthly, the job data is live. A company that started hiring last week may not be in the pool yet. Once it is in the pool, its job data is fetched fresh every day.

Job locations are free text. One company in the build sample published 13 different location strings. "Remote", "Remote - US" and "US Remote" are three different strings, and matching one does not match the others.

Some companies in the pool are not what their board suggests. A venture firm's board can carry roles for its portfolio companies. In testing, a16z's board returned 15 roles including portfolio-company positions. Read match_reason before you trust a match.

Ashby publishes no company display name. Greenhouse does, and it is often not the slug: the slug abnormalsecurity returns the name "Abnormal". Ashby's public board API returns only the jobs, so Ashby rows carry the board slug as the company name.

The filings mode covers US SEC filers only. No private companies at all. What you get in exchange is very high precision: the company said the phrase in a filing, under signature. Note that in filings mode universe_size is the number of matching filings, not the size of the searchable filer universe.

Domain resolution is imperfect. Check domain_status and domain_confidence. A low confidence match returns a null domain on purpose, because a domain you have to re-check is worse than no domain.

A retired board slug returns a 404 and is skipped. That is normal monthly churn. It is counted in the run log, never emitted as a row and never raised as an error.

❓ FAQ

Where do the companies actually come from?

The hiring mode's candidate pool is enumerated from the Common Crawl URL index, a free, openly published index of the web. The actor reads only the URL index, never archived page content. Every company running a public Greenhouse or Ashby board has board URLs in that index. The filings mode queries SEC EDGAR full text search directly, and one request answers the whole query.

Why did I get exactly one row back?

Your query matched nothing. That row has is_summary_row: true, fetch_status: "no_results" and a populated universe_size, so you can see the query ran against the whole pool and matched none of it. It is not billed.

What does universe_error mean?

The candidate pool itself could not be loaded, so there is no honest denominator. universe_size comes back null rather than 0.

How often is the pool rebuilt?

Complete unions are cached 30 days, because Common Crawl publishes about monthly and rebuilding faster just re-downloads the same index. Partial unions are held 24 hours so the next run retries for the full union. Set refresh_universe to force a rebuild.

Does it read job descriptions?

No. Greenhouse job bodies are explicitly not requested, so that text never enters the process at all. The actor cannot extract recruiter names or email addresses because it never sees them.

🧩 Want other GTM data?

Mamba Labs builds custom actors for B2B go-to-market teams. The public versions of that work live here on the Store, so our users get the same tooling we build under contract.

🧑‍💼 GTM Hiring Signal Scraper	🧱 Tech Stack Detector
📡 B2B Buying Signals Aggregator	🔑 Job Board Keyword Scanner
🔗 Domain to LinkedIn URL Resolver	🎯 ICP Fit Scorer
📋 Job Posting Monitor	📬 Domain Deliverability Checker
🏢 Company Firmographic Enricher	🌐 Company Social Presence Mapper
🪪 Company Identity Resolver	💰 Funding and Press Signal Scanner
🔄 Company Change-Event Feed	👤 People Finder and Email Verifier
🚀 Prospect Engine	🤖 AI Tooling Detector
📮 Outbound Stack Detector	📝 Publishing Frequency Tracker
✉️ Work Email Waterfall Finder	⏩ Sequencer Lead Push
🏅 Workplace Program Detector	👥 Team Page People Extractor

Every actor in the suite takes a domain or a company and returns one flat row, so they stack in the same Clay table without reshaping anything.

🛠️ Need something custom built for you or your team? Tell us what you are trying to find and we will build it. Talk to Mamba Labs.

🆘 Support

Something wrong, or a market the actor covers badly? Open an issue on the Issues tab with the input and the rows, and we will look at it.

ℹ️ Sourcing and legal. The candidate pool comes from the Common Crawl URL index, which is openly published, and the job data from the companies' own public job board APIs. Filings come from SEC EDGAR. The actor emits company names, board slugs, job titles, location strings, tickers and CIKs. It does not read job descriptions and cannot extract recruiter names or email addresses. You are responsible for how you use the output.

Built by Mamba Labs.