Funding and Press Signal Scanner

💰 What can Funding and Press Signal Scanner do?

Give it a company domain and it returns that company's recent business events: funding rounds, executive moves, product launches, acquisitions, partnerships and IPOs. One flat row per company, with the events typed and deduplicated across outlets.

It searches public news and press sources, classifies each story into a typed event, collapses the same event reported by several outlets into one, and tells you how many sources corroborated it.

📦 What you get	⚙️ Features and integrations
💰 Six typed event types with amount and stage 🔁 Cross-source dedupe with a corroboration count 🎯 Subject relevance filter, not just a mention 🧾 19 flat fields, snake_case, one row per company	📰 Google News RSS as the primary source 📣 Press wires: PR Newswire, Business Wire, GlobeNewswire ⚡ No browser, no proxy, no API keys ⬇️ Export to JSON, CSV, Excel, HTML or XML

Bought by Clay users, RevOps teams and outbound agencies who want account signals without paying for a Crunchbase seat.

🚫 This is a news signal, not a funding database. Amounts come from what outlets reported, not from filings or a licensed dataset. It will miss a round nobody wrote about, and it does not claim to be an audited funding history.

💡 Why use Funding and Press Signal Scanner?

If you want	Read these fields
A one-field buying signal	has_recent_funding
A reason to reach out today	most_recent_headline, most_recent_event_type
Recency for prioritization	latest_event_date
Rough capital raised	funding_total_estimated, funding_total_currency
Event-level detail	events, total_events
Coverage transparency	sources_queried

🎯 The subject relevance filter is the whole difference

Events are kept only when the company is the actual subject of the story, not merely mentioned in it.

"Stripe raises" stays. "Stripe-backed startup raises" is dropped.

Without that filter, every well-known company in your list picks up the funding events of everyone in its ecosystem, and a funding trigger campaign fires on the wrong accounts. It is the single most load-bearing rule in the actor.

A headline must match the company, not just its name. Since 2026-10-12 an event counts only when the headline or snippet names the company's domain, the story comes from the company's own site, or the headline uses the name as a proper noun that resolves to this company. "SpaceX IPO instantly ranks" is not about instantly.ai, and "Ramp Network raises" is not about ramp.com. Names are compared with the same normalization the Company Identity Resolver uses. Where a capital letter proves nothing, at the start of a headline or in a Title Case headline, the company must also be the subject of the event.

🔁 More sources means higher confidence, not more rows

The same funding round reported by three outlets collapses into one event carrying a corroborating_source_count. Three sources is a stronger signal than one, and it should not read as three separate raises.

▶️ Ready-to-run examples

Example	What it does
Recently Funded Company Check	Has this company raised recently
Bulk Funding Signal Scan	Scan a whole list of domains for funding
Executive Move News Tracker	Find leadership changes
Product Launch Announcement Scanner	Find recent launches
Acquisition and M&A News Finder	Find acquisitions and mergers

📋 What data can Funding and Press Signal Scanner extract?

19 fields per company. Read the summary fields for a quick answer, or unnest events for event-level workflows.

Field	What it holds
has_recent_funding	The one-field signal
latest_event_date	Most recent event, as an article publish date
most_recent_event_type, most_recent_headline	What happened, in the outlet's words
funding_total_estimated, funding_total_currency	Rough sum of the rounds detected, in USD. Reports of one round (the same stage, or amounts within 25 percent of each other within 60 days) count once, at the figure most sources gave. A valuation is never read as a raise
total_events	How many survived classification and dedupe
events	The full array. Each event carries event_type (funding_round, exec_move, product_launch, acquisition, partnership or ipo), date, headline, source_url, source_name, amount, currency, funding_stage, names, description, and corroborating_source_count. source_url is the publisher's article link; when Google News will not resolve one, it stays the Google News link
company_domain, company_name	The identity the events were attributed to
sources_queried	Which sources answered on this run
signal_types_requested, lookback_days	The filter and window this row was searched with
run_date	When the run happened
degraded, degradation_reason	Whether the sources could not be reached, and why
row_status	ok or degraded
error_reason	Why the row is degraded; null on an ok row
billable_events_json	This row's billing receipt, for example [{"event":"apify-default-dataset-item","count":1}]

Every row carries every key. A value that is unknown is null, never a missing key.

⚠️ date is the article publish date, not the event date. It is a close proxy and usually within days, but a round announced late reads as recent. Similarly funding_total_estimated is a rough sum of reported raises over 12 months, not an all-time total and not an audited figure. Treat both as signals for prioritization, not as facts to quote in a term sheet.

⚠️ false and null mean different things on every row. false is a measurement: the actor looked and the answer was no. null is the absence of one: the actor could not look. When something it needed fails, the row comes back with degraded: true, a plain-language degradation_reason, and every field it could not measure set to null rather than to a confident false or 0. Filter on degraded before you trust a negative.

🛠️ How to find a company's recent funding and press

1. Open the Input tab and put a bare domain in domain.
2. Add company_name if the domain and the trading name differ. It sharpens attribution.
3. For a list, use domains instead.
4. Click Start.
5. Read has_recent_funding for the gate and most_recent_headline for the opener.

🧪 Using it in Clay

Add an Apify enrichment column and map your domain column to domain. The summary fields land as plain columns, so has_recent_funding is usable as a filter with no parsing.

Unnest events only when you need event-level rows. Most campaigns run off the summary fields alone.

🎯 Building a funding trigger campaign

Filter on has_recent_funding = true and sort by latest_event_date. Use most_recent_headline as the anchor line in the first touch, because it is the company's own news in the outlet's words, which is checkable and specific.

Pass company_name for any company whose name is a common word. See Known limits for why.

💵 How much does it cost to scan a company for funding news?

You are charged once per company scanned (the apify-default-dataset-item event).

Plan	Per company	Per 1,000 companies
Free	$0.03	$30.00
Bronze	$0.0285	$28.50
Silver	$0.027	$27.00
Gold	$0.0255	$25.50

There is also a start event, apify-actor-start, at $0.00005, charged once per run per GB of memory.

Free plan monthly cap

Free Apify plan users get 100 results per calendar month, reset each month. A run that reaches the cap stops and says so in the status message. Paid Apify plans are not capped.

Maximum charge

The actor honors the maximum cost per run you set in Apify: when the platform reports that limit reached, the run stops cleanly and keeps every row already charged. You can also set max_charge_usd on the Input tab as a second ceiling; the run stops before any charge that would cross it.

💳 A company with no news is still billed. The actor queried every source, classified what came back and found nothing that passed the relevance filter, and "this company has been quiet" is a real answer worth having. Repeat scans of the same domain inside 24 hours are served from cache.

⌨️ Input

Everything is on the Input tab. Provide either domain or domains; neither is required on its own, and a run with neither stops with a message naming both.

Field	Type	Default	What it does
domain	string	none	Bare company domain.
company_name	string	none	Improves attribution when the trading name differs from the domain.
domains	array	none	Batch. One row per domain.
signal_types	array	all	Report only these event types.
lookback_days	integer	365	How far back to search, in days.
max_charge_usd	number	none	Optional ceiling in USD for this run's charges. The run stops before crossing it.

🎯 Asking for one kind of news

signal_types narrows the scan to the event types you care about. Six are available and they are exactly the six the classifier produces:

funding_round, ipo, acquisition, exec_move, product_launch, partnership.

{ "domain": "stripe.com", "signal_types": ["funding_round"], "lookback_days": 90 }

Narrowing narrows the search as well as the answer. A funding only scan issues one news query instead of four, so it is faster and lighter on the sources. The press wire and web fallbacks always run, because a wire release does not announce its own category.

lookback_days sets the window, default 365. Shorten it for trigger based outbound, where a raise from eleven months ago is not a trigger. Both settings come back on every row as signal_types_requested and lookback_days, so a row with one event is never confused with a row where only one type was searched.

📤 Output

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

{
  "company_domain": "stripe.com",
  "company_name": "Stripe",
  "total_events": 7,
  "latest_event_date": "2026-07-28",
  "has_recent_funding": true,
  "funding_total_estimated": 694000000,
  "funding_total_currency": "USD",
  "most_recent_event_type": "product_launch",
  "most_recent_headline": "Stripe launches new billing tools for AI companies",
  "events": [
    {
      "event_type": "funding_round",
      "date": "2026-03-11",
      "headline": "Stripe raises at a higher valuation",
      "source_url": "https://example.com/story",
      "source_name": "Example News",
      "amount": 694000000,
      "currency": "USD",
      "funding_stage": "Series I",
      "names": [],
      "description": null,
      "corroborating_source_count": 3
    }
  ],
  "signal_types_requested": null,
  "lookback_days": 365,
  "sources_queried": ["google_news", "pr_newswire", "business_wire"],
  "run_date": "2026-06-21T16:51:06Z",
  "degraded": false,
  "degradation_reason": null,
  "row_status": "ok",
  "error_reason": null,
  "billable_events_json": "[{\"event\":\"apify-default-dataset-item\",\"count\":1}]"
}

💡 Tips

• Gate on has_recent_funding and sort by latest_event_date. That is the whole funding-trigger play in two fields.
• Pass company_name for anything with a common-word name. It is the cheapest accuracy improvement available here.
• Prefer events with a high corroborating_source_count when you are going to quote them.
• Run it monthly on your target list rather than once. The value is in catching the event while it is still recent.

⚠️ Known limits

date is the article publish date, a close proxy for the actual event date rather than the event date itself.

funding_total_estimated is a rough sum of raise amounts detected in the last 12 months, not an all-time funding total. News does not always let rounds be separated perfectly.

Company matching checks identity, and a strict check can miss real news. A headline that names a common-word company in lowercase, or names it inside a longer capitalized phrase, is dropped. That keeps out news about other firms and about the word itself, at the cost of some real stories about the company. Two firms with an identical name and no domain in the story still cannot be told apart. Passing company_name with the exact trading name helps.

Person names in exec_move events are best effort and not verified.

Up to 50 most recent events are returned per company, looking back about 12 months.

Sources are public and English language, US edition. No login-gated sources, no paywalled articles, no Crunchbase, no PitchBook.

No proxy is used by default. If a source is unreachable it is skipped and the run still completes, with sources_queried showing what actually answered.

❓ FAQ

Is this legal?

The actor reads public news and press pages only. It does not access login-gated or paywalled sources, and it does not scrape Crunchbase or PitchBook.

How fresh is the data?

Each scan looks back about 12 months and returns the most recent events first. Repeated scans of the same domain within 24 hours are served from cache.

Why did a company I know raised come back with nothing?

Either it was not covered by an English-language source in the window, or the story did not pass the subject relevance filter. sources_queried shows what answered.

Why is one funding round showing as one event when three outlets covered it?

That is the dedupe working. Check corroborating_source_count on the event.

Can I get event-level rows instead of one row per company?

Unnest the events array downstream. The actor emits one row per company by design so it drops into a company table without reshaping.

🧩 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.

🔭 Account Hiring Watch	🕵️ Agent Accessibility Auditor
🤖 AI Tooling Detector	📡 GTM Signals Aggregator
🚀 Prospect Engine	📝 Publishing Frequency Tracker
🦋 Bluesky Brand Presence Mapper	🔀 Career Change Signal Engine
⏩ Sequencer Lead Push	🔄 Company Change Event Feed
📇 Company Contact Details Extractor	🧭 Company Discovery List Builder
🏢 Company Firmographic Enricher	🪪 Company Identity Resolver
🌐 Company Social Presence Mapper	🏷️ Contact Classifier
📈 Influencer Change Monitor	🔎 Influencer Finder
🧾 Influencer Lead List Builder	👤 Influencer Profile Scraper
📬 Domain Deliverability Checker	🔗 Domain to LinkedIn URL Resolver
🛒 Ecommerce Platform Profiler	✉️ Work Email Waterfall
🎪 Event Presence Index	⚖️ Expert Witness Directory
💵 Company Funding Record	🐙 GitHub Organization Signal Scanner
🧑‍💼 GTM Hiring Signal Scraper	📋 Job Posting Monitor
🧱 Tech Stack Signal Detector	🎯 ICP Fit Scorer
🔑 Job Board Keyword Signal Scanner	🔁 Job Change Tracker
🏛️ Legal Entity Resolver	📰 Link in Bio Scraper and Newsletter Detector
💼 LinkedIn Company Page Mapper	💬 LinkedIn Post Tracker
📢 Meta Ad Library Monitor	📸 Instagram Facebook Brand Presence Mapper
🆕 New Hire Finder	📮 Outbound Stack Detector
📄 Page Finder and Extractor	🧑 People Finder & Email Verifier
📌 Pinterest Brand Presence Mapper	🏆 Government Contract Award Monitor
📅 Reporting Window Finder	👽 Reddit Brand Presence Mapper
⭐ Trustpilot Reputation Enricher	🤝 Influencer Talent Agency Lookup
👥 Team Page People Extractor	🎵 TikTok Brand Presence Mapper
📊 Website Traffic Rank Estimator	🏅 Workplace Program Detector
✖️ X Brand Presence Mapper	▶️ YouTube Channel Stats 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 an event attributed to the wrong company? Open an issue on the Issues tab with the domain and the event, and we will look at it.

ℹ️ Sourcing and legal. Events come from public news and press pages: Google News RSS, PR Newswire, Business Wire, GlobeNewswire and public search. No login-gated or paywalled sources are accessed, and no licensed funding database is used. Executive names appear as published in the article and are not independently verified. You are responsible for how you use the output.

Built by Mamba Labs.