Wellfound Startup Scraper — Founders, Websites & Funding

Build a list of startups from Wellfound (formerly AngelList Talent) by market, city or tech stack. Every startup comes back as one row with its own website, one-liner, description, headcount band, stage, markets, offices, open jobs, its founders (name, title, tenure, location, Wellfound profile), funding raised and latest round, and HQ address — plus the email, phone and company LinkedIn / X / Facebook links published on the startup's own website.

It is built for people who sell to startups: agencies, SaaS sales teams, recruiters, investors and service providers who need the decision-maker and a way to reach them, not just a company name.

What one row looks like

A real row from a verified run (search: Fin Tech in New York, run 2026-09-30; long arrays shortened):

{
  "startupId": "177310",
  "name": "Riskified",
  "slug": "riskified",
  "wellfoundUrl": "https://wellfound.com/company/riskified",
  "website": "https://www.riskified.com/",
  "websiteDomain": "riskified.com",
  "oneLiner": "Riskified makes eCommerce safe, accessible, and frictionless",
  "companySize": "501-1000",
  "stage": "public_stage",
  "stageLabel": "Public Stage",
  "businessModel": "B2B",
  "hasTopInvestors": true,
  "glassdoorRating": 4.5,
  "markets": ["E-Commerce", "Payments", "Machine Learning", "Fraud Detection", "Risk Management", "Fin Tech"],
  "locations": ["New York City", "New York", "Tel Aviv-Yafo"],
  "hqCity": "New York",
  "hqRegion": "New York",
  "hqCountry": "United States",
  "founders": [
    {
      "name": "Assaf Feldman",
      "title": "Founder",
      "profileUrl": "https://wellfound.com/p/assaf-feldman",
      "linkedinUrl": "http://www.linkedin.com/pub/assaf-feldman/0/167/991",
      "avatarUrl": "https://photos.wellfound.com/users/285286-medium_jpg?1463375411"
    },
    { "name": "Eido Gal", "title": "Founder", "profileUrl": null, "linkedinUrl": null }
  ],
  "founderNames": "Assaf Feldman; Eido Gal",
  "primaryFounderName": "Assaf Feldman",
  "primaryFounderTitle": "Founder",
  "primaryFounderLinkedinUrl": "http://www.linkedin.com/pub/assaf-feldman/0/167/991",
  "email": "hello@riskified.com",
  "emails": ["hello@riskified.com", "riskified.china@riskified.com", "japan@riskified.com", "press@riskified.com"],
  "companyLinkedinUrl": "https://www.linkedin.com/company/riskified",
  "companyFacebookUrl": "https://www.facebook.com/RiskifiedInc",
  "companyInstagramUrl": "https://www.instagram.com/riskified",
  "contactSourceUrl": "https://www.riskified.com/contact/",
  "totalRaisedText": "$230.3M",
  "totalRaisedUsd": 230300000,
  "fundingRoundsCount": 6,
  "latestRoundDate": "Nov 2019",
  "latestRoundAmountUsd": 165000000,
  "openJobsCount": 29,
  "openJobsByRole": [{ "role": "Engineering", "count": 11 }, { "role": "Sales", "count": 5 }],
  "openJobs": [
    {
      "jobId": "3544615",
      "title": "Senior Global Revenue Enablement Manager",
      "url": "https://wellfound.com/jobs/3544615-senior-global-revenue-enablement-manager",
      "compensation": "$140k – $150k",
      "employmentType": "Full Time",
      "locationAndRoleTags": ["New York", "BD Manager"]
    }
  ],
  "enrichment": "full",
  "foundVia": "Fin Tech in New York",
  "sourceUrl": "https://wellfound.com/startups/l/new-york/fintech-2"
}

How to use it

Pick what to search, set how many startups you want, run.

All fintech startups in London

{ "markets": ["Fin Tech"], "locations": ["London"], "maxResults": 200 }

AI and health-care startups in New York and San Francisco, early and growth stage only, with founder LinkedIn links

{
  "markets": ["artificial intelligence", "health care"],
  "locations": ["New York", "San Francisco"],
  "stages": ["early_stage", "growth_stage"],
  "includeFounderProfiles": true,
  "maxResults": 500
}

Every startup that uses Python, B2B only

{ "technologies": ["python"], "businessModel": "B2B", "maxResults": 0 }

Specific startups you already know (slugs or URLs), or a Wellfound directory page as it is:

{ "startups": ["gustohq", "https://wellfound.com/company/moderntreasury", "https://wellfound.com/startups/l/london/fintech-2"] }

With no input at all the actor lists the first 50 startups of Wellfound's whole directory.

Markets and locations are typed the way you would say them

"Fin Tech", "fintech", "AI", "health care", "New York City", "NYC", "remote" all work. Behind them are Wellfound's own slugs (fintech-2, artificial-intelligence, new-york, remote-friendly), resolved from Wellfound's list of 802 markets and 305 locations.

Wellfound does not reject a filter it does not know. It silently drops it and serves its whole directory of ~10,000 startups with a normal-looking page — ask for /startups/industry/fintech (the real slug is fintech-2) and every startup on the site comes back labelled as fintech. Every search here is checked against the filter Wellfound says it actually applied before a single row is kept. A search it did not apply is skipped, costs nothing, and the run summary lists close matches (e.g. fintech (fintech-2)).

Each market × location pair is one search when both are given (turn off Combine each market with each location to search them separately). A technology is always its own search — Wellfound cannot combine it with a market or a city.

Input

Field	What it does	Default
markets	Markets / industries, as text or Wellfound slugs	—
locations	Cities, regions, countries, or remote	—
technologies	Tech-stack slugs (python, react, aws)	—
combineMarketAndLocation	Each market × each location is one search	true
startups	Company slugs / URLs to look up, and/or Wellfound directory URLs (a ?page=N URL starts at that page)	—
maxResults	Startups for the whole run; 0 = no limit	50
maxPagesPerSearch	Directory pages per search (10 startups a page); 0 = all	0
stages	Keep only early_stage, growth_stage, scale_stage, public_stage	all
companySizes	Keep only these bands: 1-10 … 5000+	all
businessModel	any, B2B or B2C	any
onlyYcBacked	Only startups with Wellfound's Y Combinator badge	false
onlyTopInvestors	Only startups with the Top Investors badge	false
requireWebsite	Skip startups without a website of their own	false
requireFounders	Skip (and do not charge) startups with no listed founder	false
includeFounders	Founders, funding, HQ, team background (one job page per startup)	true
includeOpenJobs	Attach the open jobs list	true
maxOpenJobsPerStartup	Cap on the openJobs array (openJobsListed is always the full count)	25
includeWebsiteContacts	Email, phone and company socials from the startup's own website	true
includeFounderProfiles	LinkedIn / X / GitHub / site links from each founder's public Wellfound profile	false
concurrency	Startups enriched in parallel	4
proxyConfiguration	Leave empty for the automatic route (see How it gets the data)	automatic

The stage / size / model / YC / investor / website filters are applied to the directory card before any extra page is opened, so a filtered-out startup costs nothing.

Output fields

Company

Field	Description
startupId	Wellfound's numeric startup id — the dedupe key
name, slug, wellfoundUrl	Name, Wellfound slug and profile URL
website, websiteDomain	The startup's own site (never a Wellfound URL)
oneLiner, description	Wellfound pitch line and long description
logoUrl	Logo image
companySize, companySizeRaw, employeesText	Employee band (51-200), Wellfound's code (SIZE_51_200), the band as the job page prints it
stage, stageLabel, companyTypes	early_stage / growth_stage / scale_stage / public_stage and its label
businessModel	B2B, B2C or B2B/B2C
isYcBacked, hasTopInvestors, valuationTier, isGrowingFast, isRecentlyFunded, isActivelyHiring	Wellfound's badges as columns (valuationTier = 1B+ / 500M+)
glassdoorRating, glassdoorLeadershipRating, glassdoorWorkLifeBalanceRating	The ratings Wellfound shows beside its "Highly rated" badges — they are Glassdoor's, which only Wellfound's tooltip says. Empty = no badge, not a low score
responseSpeed, isTopResponder	How fast the startup answers applicants
badges	Every badge with its label and tooltip
markets, marketSlugs, locations, locationSlugs	Market and office tags
hqCity, hqRegion, hqCountry, hqLatitude, hqLongitude	Headquarters from the job posting's structured data

People and contact

Field	Description
founders[]	name, title, tenure ("8 years"), location, profileUrl, avatarUrl, and with founder profiles on: linkedinUrl, twitterUrl, githubUrl, personalWebsite
foundersCount, foundersListMayBeTruncated	How many are listed; true when 3 are shown (Wellfound's card shows at most 3)
founderNames	All listed founders, ;-separated (CSV-friendly)
primaryFounderName, primaryFounderTitle, primaryFounderProfileUrl, primaryFounderLinkedinUrl	The CEO if one is listed, else the first founder
email, emails	Best address from the startup's website (sales/contact/hello first), and all of them — only addresses on the startup's own domain or a freemail box
phone, phones	Phone numbers the website publishes as tel: links or structured data
companyLinkedinUrl, companyTwitterUrl, companyFacebookUrl, companyInstagramUrl, companyYoutubeUrl	The company's social profiles as linked from its website
contactSourceUrl, websiteReachable	The page the email/phone came from; whether the site answered

Funding and hiring

Field	Description
totalRaisedText, totalRaisedUsd	Amount raised as Wellfound prints it, and in dollars ("Undisclosed" stays null)
fundingRoundsCount, latestRoundName, latestRoundDate, latestRoundAmountUsd	Round count and the latest round
openJobsCount, openJobsListed, openJobsByRole	Open roles (Wellfound's count, the listed count, per department)
openJobs[]	jobId, title, url, compensation (salary and/or equity), employmentType, locationAndRoleTags (Wellfound's own tags in its order — a multi-city job lists every city, so they are not split into guessed columns)
teamPreviousEmployers[]	"Employees joined from": companies the team was hired from, with their websites

Provenance: enrichment (full, jobs-only, job-page-unreachable, off), jobPageUrl, foundVia, sourceUrl, sourcePage, scrapedAt.

Measured coverage

From real runs on the Apify platform (2026-09-29/30). How full a column is depends on which startups you search — the well-known names at the top of a market are complete, the small ones deep in a tech list are thin — so each field is given as the range across four different searches.

Field	Fin Tech top 50	Health care top 50	AI in San Francisco (60)	Python, pages 40–44 (50)
website	100%	100%	100%	100%
one-liner / size / markets / locations / open jobs	100%	100%	98–100%	98–100%
stage	100%	100%	78%	98%
founders (≥1 named)	90%	86%	77%	40%
funding raised	90%	82%	60%	86%
HQ city	56%	44%	78%	16%
email (from website)	—	62%	—	—
company LinkedIn (from website)	—	72%	—	—

With every option on (Fin Tech in New York, 20 startups): founders 95%, email 35%, company LinkedIn 90%, company X 85%, funding 80%, HQ 90%, founder LinkedIn 30% (only founders who keep a public Wellfound profile list one — between 9% and 35% of founders do, depending on the search; of those, 27 of 28 in the Fin Tech run listed a LinkedIn).

Every founder shown is a real current founder: checked against Wellfound's full team page on 16 startups, the names matched on all 15 with three or fewer founders.

Pricing

$1.30 per 1,000 startups ($0.0013 each), pay per result. No start fee, no monthly fee.

• One charge per distinct startup per run, keyed on Wellfound's startup id. A startup found by three of your searches is delivered and charged once.
• Founders, funding, HQ, open jobs and website contacts are included in that price.
• Never charged: startups removed by your filters, searches Wellfound does not recognise, look-ups that do not exist or have no open job, and anything that could not be read.
• Examples: 100 startups = $0.13 · 1,000 = $1.30 · all ~380 fintech startups = about $0.50.

Data limits

• Founders come from the "Founders" card Wellfound prints on each job page, which shows at most three. A startup with more founders gets its first three (foundersListMayBeTruncated: true flags a full card). Non-founder team members, board members and investor names are only on Wellfound's company pages, which sit behind a Cloudflare challenge — they are not included.
• Founders and funding need one open job. Wellfound publishes a startup's founders and funding on its job pages; the directory lists hiring startups, so almost every directory row has one. A looked-up startup with no open job is listed in the run summary and not delivered.
• Round-by-round funding history (every round, its investors, valuations) is not included: only the total, the round count and the latest round, as the job page shows them.
• Founder LinkedIn exists only for founders who keep a public Wellfound profile (9–35% of founders, by search).
• HQ comes from the job posting's structured data; many startups do not fill it — the locations tags are always there.
• Email / phone come from the startup's own website, not from Wellfound (Wellfound publishes none). Sites that show only a contact form give no email.
• Headcount is Wellfound's self-reported band, not an exact number.
• Stage, badges and ratings are on directory results. A startup fetched by slug in startups has no directory card, so those columns are empty for it (stage is taken from the job page when it prints one).
• Wellfound's directory holds about 10,250 startups in total.

How it gets the data

1. Directory — Wellfound's public startup directory pages (/startups/industry/…, /startups/location/…, /startups/l/<city>/<market>, /startups/tech/…), 10 startups a page, until your cap or the last page.
2. Open jobs — the startup's public jobs widget, which lists every open role.
3. Founders, funding, HQ — the startup's newest job page.
4. Website contacts — the startup's homepage, plus up to two contact/about pages when the homepage shows no email.
5. Founder profiles (optional) — each founder's public Wellfound profile.

No login and no browser. Requests go out directly first; if Wellfound starts answering one kind of page with a "Security Check", that kind of page moves to Apify datacenter and then residential proxies for the rest of the run, automatically. Set a proxy in Proxy to use only that one.

Run summary

Every run writes RUN_SUMMARY to its key-value store:

• per search: the URL used, the filter Wellfound applied, its total startup count, pages read, startups delivered and why the search stopped;
• searches Wellfound did not recognise, with close matches;
• look-ups not found / without an open job / unreachable;
• how many startups your filters removed, duplicates skipped, founders and emails found;
• a per-page-type request log (direct / datacenter / residential, answered / blocked).

Runs save their progress after every page, so a run the platform moves to another server picks up where it stopped without delivering or charging anything twice.

FAQ

Why did my search return startups from other markets? It cannot: a search whose filter Wellfound did not apply is dropped before any row is kept. Check RUN_SUMMARY.unresolved for the slug it suggests.

How do I get every startup in a market? Set maxResults to 0. Fintech is ~380 startups (38 pages), health care ~780, the whole directory ~10,250.

Why is founders empty for some startups? Their Wellfound page lists no founder. Turn on requireFounders to skip them without paying.

Why is the email a support@ or press@ address? It is the best one the website publishes; emails has the full list, sales/contact/hello-style inboxes first.

Can I search by a keyword that is not a market? Use the closest Wellfound market (the summary suggests them) or a technology.

Can I combine a technology with a city? Not in one search — Wellfound's directory does not. Run the technology, then filter on locations.

Does it find startups that are not hiring? Wellfound's directory lists hiring startups. A non-hiring startup can be looked up by slug, but without an open job its founders and funding are not published.

Why do two runs of the same search differ slightly? Wellfound reorders its directory and startups open and close jobs daily; the totals move by a few.

How fast is it? About 50 startups a minute with the default options at 512 MB.

Is the same startup charged twice across runs? Within a run, never. Across separate runs, each run charges for what it delivers.