BetaList Scraper - Startup Profiles, Founders & Contacts

BetaList Scraper: Startup Profiles, Websites and Contacts

BetaList Scraper turns BetaList into structured startup data. Discover newly launched and upcoming startups by keyword, topic, region or the latest feed, or paste exact BetaList links, then get each startup's full profile: tagline, description, topics, regions, feature date, screenshots and the resolved company website. Turn on contact enrichment to also pull public emails, phone numbers and social profile links straight from the startup's own site, then export to JSON, CSV or Excel, or read the results through the API.

Why This Scraper?

• Two ways to source. Search by keyword, topic, region or the latest feed, or paste exact BetaList links, including a single startup page.
• Full startup profile. Name, tagline, description, topics, regions, feature date, screenshots and logo, plus the resolved company website behind BetaList's own redirect link.
• Contacts on demand. Turn on contact enrichment to pull public emails, phone numbers and social profile links (LinkedIn, X, Facebook, Instagram, YouTube, GitHub and more) straight from the startup's own site.
• Filters that matter. Boosted-only, and a feature-date window to keep only startups launched in a given range.
• Deep, budgeted collection. Walk as many result pages as you choose per source, capped by Max startups so cost stays predictable.
• Built for monitoring. Incremental mode tracks the same search over time and returns only what's new or changed, and Resume continues one interrupted run without paying twice.

Use Cases

• Investors and scouts: track newly launched startups by topic or region to build a fresh deal-sourcing list.
• Sales and growth teams: build prospect lists with verified websites, emails and social profiles for outbound outreach.
• Market researchers: map which topics and regions are trending on BetaList over time.
• Founders and PR teams: monitor competitors' launches, taglines and feature dates.
• Newsletter and content creators: source fresh startup profiles for roundups and features.

Data You Get

Sample shape: values are illustrative placeholders, not from a live listing.

Field	Example
name	"Sample Startup"
one_liner	"A short one-line pitch for the product"
description	"Full description text appears here when detail pages are fetched."
url	"https://betalist.com/startups/sample-startup"
slug	"sample-startup"
website_url	"https://sample-startup.example.com"
website_domain	"sample-startup.example.com"
boosted	false
featured_at	"2026-01-01"
featured_date_label	"January 1, 2026"
topic_names	["Artificial Intelligence", "Productivity"]
regions	[{ "name": "California", "slug": "california" }]
primary_image_url	"https://images.betalist.com/startup/sample-startup/cover.jpg"
makers / maker_name / maker_link / maker_identifier	[{ "name": "Sample Maker", "handle": "samplemaker", "url": "https://betalist.com/@samplemaker" }] (first maker in the flat fields; empty when the profile lists none; needs detail pages)
product_name, long_description, website, featured_date	Aliases of name, description, website_url, featured_at for drop-in compatibility
image_urls	["https://images.betalist.com/startup/sample-startup/cover.jpg"]
logo_url	"https://cdn.betalist.com/000000"
similar_startups	[{ "name": "Another Sample Startup", "slug": "another-sample-startup" }]
contacts.emails	["hello@example.com"]
contacts.phone_numbers	["+10000000000"]
contacts.social_media	{ "linkedin": "https://www.linkedin.com/company/example" }
id	10000001

BetaList does not publish user reviews, ratings or comments on startup pages, so this actor produces none. The site also does not expose a distinct "launched" or "removed" status on a startup profile itself: whether a startup is still findable on the same search, topic, region or the latest feed run to run is the only lifecycle signal available, and Incremental mode's changeType tracks that presence over time (see How to Use below). The only other social signal on a profile page is the "Similar startups" suggestions, captured in similar_startups.

How to Use

1. Pick a mode: search (by keyword, topic, region or the latest feed) or url (paste exact BetaList links, including a single startup page).
2. For search mode, fill in keywords, a topic or a region (names such as Artificial Intelligence or California, or slugs such as california; a topic or region BetaList does not serve fails the run with a clear error), plus any filters; for url mode, paste the links. When urls is omitted from the input (API calls), url mode scrapes (a behaviour change from earlier versions) six examples (previously nothing): the latest feed, a keyword search (ai), a browse topic (Artificial Intelligence), a region (California), a country region (United States) and a single startup page (Agent UI). The Console form starts pre-filled with example links of every supported shape (including paginated, sorted and www./http:// variants); replace them with your own links before running.
3. Turn on Fetch detail pages and/or Enrich with contacts for full profiles and contact signals, and set Max startups to control run size and cost.
4. Click Start, then download the dataset as JSON, CSV or Excel, or read it through the API.

Search by keyword:

{
  "mode": "search",
  "queries": ["ai", "fintech"],
  "maxItems": 50
}

Search a topic with full profiles and contact enrichment:

{
  "mode": "search",
  "topic": "artificial-intelligence",
  "getContacts": true,
  "fetchDetails": true,
  "maxItems": 25
}

Boosted startups only, for a keyword:

{
  "mode": "search",
  "queries": ["ai"],
  "boostedOnly": true,
  "maxItems": 20
}

Paste exact BetaList links (a topic page and a single startup page):

{
  "mode": "url",
  "urls": [
    "https://betalist.com/topics/artificial-intelligence",
    "https://betalist.com/startups/autobound"
  ],
  "maxItems": 30
}

Run it from your code

Python:

from apify_client import ApifyClient

client = ApifyClient("<YOUR_APIFY_TOKEN>")
run = client.actor("abotapi/betalist-com-scraper").call(run_input={"mode": "search", "queries": ["ai"], "maxItems": 20})
for startup in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(startup["name"], startup["website_url"])

JavaScript:

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: '<YOUR_APIFY_TOKEN>' });
const run = await client.actor('abotapi/betalist-com-scraper').call({ mode: 'search', queries: ['ai'], maxItems: 20 });
const { items } = await client.dataset(run.defaultDatasetId).listItems();

Or connect it to Make, Zapier, n8n, Google Sheets or webhooks from the Integrations tab.

How Max startups and Max pages work together

Max startups is the run's real budget: the actor stops pushing new records once it is reached, and splits that budget evenly across every keyword, topic, region or URL you gave it. Max pages is only a per-source safety ceiling on how many result pages to walk looking for that budget; leave it at the default unless a single source needs to page unusually deep. Boosted-only and feature-date filters drop cards after they are fetched, so a heavily filtered search may return fewer startups than Max startups even before either limit is reached.

Resume and recurring updates

Two different features, both off by default so existing behavior is unchanged:

• Resume (resumeFromRunId): paste a previous run ID or dataset ID to continue one specific interrupted collection. A startup slug already saved there is never pushed or billed again. For a pasted single-startup URL this also skips fetching it entirely. For search, topic, region and latest-feed sources, the run still walks each source's result pages from the start (or from the page number encoded in a pasted URL), checking every card against the already-saved list, so a resumed run on a large source still fetches as many pages as a fresh one, it just avoids re-pushing and re-billing what it already has. Max startups still caps only the new startups pushed this run. If the pasted ID does not match a run or dataset this Apify account can read, the run fails immediately with a clear message instead of silently starting over.
• Incremental mode (incrementalMode): turn on for daily or recurring monitoring of the same search. The actor remembers the previous run's results itself (keyed on mode plus keywords/topic/region/URLs, the filters, and fetchDetails, or your own stateKey) and classifies every startup as NEW, UPDATED (with changedFields), UNCHANGED, REAPPEARED or EXPIRED. UNCHANGED startups are suppressed (not returned, not billed) unless emitUnchanged is on. A startup is only ever recorded as gone, and only then eligible to come back as REAPPEARED later, after a run with emitExpired on that was not resumed, did not hit Max startups, and reached the natural end of every tracked source; emitExpired also gates whether the EXPIRED row itself is returned and billed that run. A capped, resumed or partial run never marks a still-live startup as gone, and leaves its previously saved state untouched. Setting resumeFromRunId while incrementalMode already has saved state for that same search fails the run rather than silently mixing the two workflows; use a different stateKey to bootstrap a separate campaign instead.

A URL pasted with ?page=N (N above 1) starts mid-list, so it counts as a partial scan and never produces EXPIRED rows.

Dataset rows produced by Incremental mode add four bookkeeping fields: changeType, changedFields, firstSeenAt, lastSeenAt. These are absent unless incrementalMode is on.

Output views and run summary

The dataset has four views in the Console: Startups (overview), Startup details, Contacts and Changes (incremental fields). Each run also saves a small OUTPUT record in the key-value store with startups pushed, sources requested and walked, and whether every source reached its natural end.

Filters

boostedOnly keeps only Boosted startups (both modes). featuredAfter and featuredBefore (YYYY-MM-DD) keep startups featured in that window and automatically turn on detail pages. Filters drop cards after they are fetched and are ignored for pasted single-startup URLs.

Supported URL shapes

In url mode paste any of: the latest feed (https://betalist.com/), search (/search?q=ai, with &sort= and &page=), topic (/topics/<slug>, resolved to its /browse/... page so ?page=N is honoured), browse topic (/browse/<category>/<topic>), region and country pages (/regions/<slug>), or a single startup (/startups/<slug>); www. and http:// links work. Index pages (/browse, /browse/<category>, /regions) list no startups and are skipped with a warning.

Send results into your apps (MCP connectors)

Optionally pipe results into the apps you already use via Model Context Protocol (MCP) connectors. This is an extra delivery step after the scrape: the Apify dataset is never changed. Authorize a connector once under Apify, then Settings, then API & Integrations (Notion, Linear, Airtable or Apify), select it in the mcpConnectors input, and set notionParentPageUrl for the Notion connector. The connector receives a condensed, human-readable summary per startup (name, tagline, website, topics, one email or phone), not the full JSON; the complete record always stays in the Apify dataset. Leave the field empty to skip; it never changes the dataset output.

Input Parameters

Parameter	Type	Default	Description
mode	string	search	search (keywords/topic/region/latest feed) or url (paste BetaList links).
queries	array	none (input editor prefills ["ai"] as a starting example)	Keywords to search on BetaList. Search mode only.
topic	string	none	A topic name, slug or browse path to collect. Search mode only.
region	string	none	A region name or slug to collect, e.g. california. Search mode only.
boostedOnly	boolean	false	Keep only startups flagged Boosted. Applies in both modes.
featuredAfter	string	none	Keep only startups featured on or after this date (YYYY-MM-DD); setting it automatically turns on detail-page fetching, since the feature date only appears on the profile page.
featuredBefore	string	none	Keep only startups featured on or before this date (YYYY-MM-DD); setting it automatically turns on detail-page fetching.
urls	array	six examples: latest feed, keyword search, browse topic, region, country region and a single startup page (used when urls is omitted from the input via the API; the Console form starts pre-filled with more example links, so replace them with your own)	BetaList links to collect: the latest feed, search results (including &sort= and &page=), topic/browse pages, region pages, or a single startup page (www. and http:// links work). A /topics/... link is resolved to its canonical /browse/... page first, so ?page=N is honoured. Index pages (/browse, /browse/<category>, /regions) list no startups and are skipped with a warning, as is a /topics/... link to a topic BetaList does not serve. An explicit empty list scrapes nothing. URL mode only.
fetchDetails	boolean	true	Open each startup's profile page for the full description, topics, regions, feature date, screenshots and resolved website.
getContacts	boolean	false	Visit each startup's own website for emails, phone numbers and social links.
maxItems	integer	20	Maximum startups to save across the run (0 = unlimited, stops at Max pages instead).
maxPages	integer	0	Safety ceiling on pages walked per source. 0 uses the built-in limit of 200 pages per source; any positive value is used as given. The run normally stops at Max startups first.
proxy	object	Apify Proxy	Connection settings.
mcpConnectors	array	none	Send a summary of each result into apps you authorized under Integrations. Leave empty to skip.
notionParentPageUrl	string	none	Notion connector only: the page under which item pages are created.
maxNotifyListings	integer	50	Cap on items written to each connector per run. Does not affect the dataset.
resumeFromRunId	string	none	Continue one interrupted run without re-collecting or re-billing startups it already saved.
incrementalMode	boolean	false	Turn on for recurring monitoring of the same search; later runs return only what changed.
stateKey	string	none	Name an incremental-mode campaign explicitly instead of the auto-derived key.
emitUnchanged	boolean	false	Incremental mode only: also return and bill startups identical to the last run.
emitExpired	boolean	false	Incremental mode only: also mark and return (and bill for) startups no longer found, after a complete scan.
ignoreFieldsForChanges	string[]	none	Incremental mode only: field names (dot for nested, e.g. source.scraped_time) that do not count as a change. They stay in the output. These are always ignored: source.scraped_time, similar_startups and the alias fields product_name, long_description, website and featured_date (copies of tracked fields).

Output Example

Sample shape: values are illustrative placeholders, not from a live listing.

{
  "type": "startup",
  "id": 10000001,
  "url": "https://betalist.com/startups/sample-startup",
  "slug": "sample-startup",
  "name": "Sample Startup",
  "one_liner": "A short one-line pitch for the product",
  "short_description": "A short one-line pitch for the product",
  "description": "Full description text appears here when detail pages are fetched.",
  "visit_url": "https://betalist.com/startups/sample-startup/visit",
  "website_url": "https://sample-startup.example.com",
  "website_domain": "sample-startup.example.com",
  "boosted": false,
  "featured_at": "2026-01-01",
  "featured_date_label": "January 1, 2026",
  "topics": [{ "name": "Artificial Intelligence", "slug": "artificial-intelligence", "url": "https://betalist.com/browse/ai/artificial-intelligence" }],
  "topic_names": ["Artificial Intelligence"],
  "makers": [{ "name": "Sample Maker", "handle": "samplemaker", "url": "https://betalist.com/@samplemaker" }],
  "maker_name": "Sample Maker",
  "maker_link": "https://betalist.com/@samplemaker",
  "maker_identifier": "samplemaker",
  "product_name": "Sample Startup",
  "long_description": "Full description text appears here when detail pages are fetched.",
  "website": "https://sample-startup.example.com",
  "featured_date": "2026-01-01",
  "image_urls": ["https://images.betalist.com/startup/sample-startup/cover.jpg"],
  "primary_image_url": "https://images.betalist.com/startup/sample-startup/cover.jpg",
  "logo_url": "https://cdn.betalist.com/000000",
  "regions": [{ "name": "California", "slug": "california", "url": "https://betalist.com/regions/california" }],
  "similar_startups": [{ "slug": "another-sample-startup", "name": "Another Sample Startup", "url": "https://betalist.com/startups/another-sample-startup", "tagline": "A related fictional pitch", "boosted": false }],
  "contacts": {
    "emails": ["hello@example.com"],
    "phone_numbers": ["+10000000000"],
    "social_media": { "linkedin": "https://www.linkedin.com/company/example", "twitter": "https://x.com/example" }
  },
  "contacts_lookup_url": "https://sample-startup.example.com",
  "source": {
    "betalist_url": "https://betalist.com/startups/sample-startup",
    "seed_value": "https://betalist.com/topics/artificial-intelligence",
    "source_url": "https://betalist.com/startups/sample-startup",
    "scraped_time": "2026-01-01T00:00:00.000Z"
  }
}

Plan Requirement

BetaList served plain pages without any challenge, and the default Apify Proxy connection (automatic group) was measured serving its latest feed, search and startup pages, so a paid connection tier is not needed for normal runs. Apify free plans do not include Apify Proxy: on a free plan the default connection is refused, the log shows a warning that residential proxies are unavailable, and the run continues on a backup connection, logging "Served over the backup connection (the default connection was unavailable)." when a backup serves the page. On a paid plan the actor starts on the default connection (or the proxy groups you choose) and, if it is refused, retries on a residential connection and then on a backup connection. Residential traffic is billed to your Apify plan and is your choice; your own proxy URLs also work. If no BetaList page could be loaded at all, the run fails instead of returning an empty dataset, with one of these messages: "The proxy connection was refused for this account, so no page could be read. Your Apify plan does not include proxy access; a paid plan is required", "No results: residential proxies are unavailable on this run (Apify free plans do not include them), and the backup connection could not load the requested BetaList pages", or "Could not load any results page (the requests failed), so nothing was collected. This is a connection problem, not an empty search."

FAQ

How much does it cost?

Three events are charged: apify-actor-start once per run, apify-default-dataset-item once for every startup row saved to the dataset (the main charge), and detail-enrichment once for every saved row whose profile page loaded and/or whose website contact lookup ran. Fetch detail pages defaults to on, and a pasted single-startup URL always opens its profile page, so most rows carry the detail-enrichment charge even when a loaded page or the website lookup finds nothing extra. The detail-enrichment charge is made per row, right after that row is saved, never for suppressed or unchanged rows, and never for a row where the profile page failed to load and no website contact lookup ran. The Pricing tab shows current rates; use Max startups to cap the cost of any run.

Is it legal to scrape BetaList?

This actor collects only publicly available startup listing data. You are responsible for how you use it: follow BetaList's terms and the laws that apply to you, and get legal advice if you plan commercial redistribution. Contact details pulled from a startup's own website are the kind of information that site already published publicly, but you should still handle emails and phone numbers responsibly.

Can I get only new or changed startups on a schedule?

Yes. Schedule the actor from the Schedules tab and turn on Incremental mode. Later runs then classify each startup as new, updated, unchanged, reappeared or gone against the previous run for that same search, and unchanged ones are not billed unless you ask for them.

What is the difference between Resume and Incremental mode?

Resume continues one specific interrupted run using a pasted run or dataset ID, useful right after a run stopped partway through. Incremental mode is for running the same search again and again, for example daily, and remembers state itself so you only get what changed. They solve different problems and are not meant to be combined on the same tracked search.

Why did my run return fewer startups than expected, or none at all?

BetaList itself shows only the first 60 startups for a keyword search and a single page of recent startups on the latest feed, so those sources cannot return more. If BetaList pages load but the startup list on them cannot be read, the run fails with a message saying so instead of finishing empty. A boosted-only or feature-date filter can legitimately drop every card fetched, which gives a normal successful run with an empty dataset. A single source (a keyword, topic, region or feed) whose requests are all refused is skipped with a warning while other sources continue. If no BetaList page could be loaded at all, the run fails with a connection message (see Plan Requirement) rather than finishing empty. A pasted single startup URL whose page cannot be read (removed or blocked) is skipped with a warning and is not saved or charged. Check the run log for warnings, then try again or choose a residential connection group.

Can I use it with AI agents or MCP?

Yes. Call it from any Apify integration or MCP client, and use the connector field to push results into Notion, Linear or Airtable.

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