News Signals
Real-time company news events including funding rounds, acquisitions, partnerships, product launches, executive hires, and expansion announcements.
News Signals capture real-time company events from across the web — funding rounds, acquisitions, partnerships, product launches, executive hires, and expansion announcements — the moments when budgets unlock, priorities shift, and vendors get evaluated.
We monitor news sources across 4M+ companies, extracting and categorizing events into 40 subtypes. Each signal includes the source article, key sentence, and structured metadata (location, people, financing details) so you can act on timely triggers within days of publication.
A single company can produce multiple signals per week depending on news volume. Signals fire within 24–48 hours of article publication, giving you a narrow outreach window while events are still fresh.
See real delivered data → Sample Files
Subtypes represent the specific business event detected in the news — from funding rounds to executive hires to office expansions. Use them to filter for the events most relevant to your sales motion.
Available Subtypes (40)
| Subtype Enum | Description |
|---|---|
acquires | Company acquires another company or assets |
attends_event | Company attends or sponsors an industry event |
closes_offices_in | Company closes offices in a location |
declares_bankruptcy | Company declares bankruptcy or files for insolvency |
decreases_headcount_by | Company reduces workforce |
ends_partnership_with | Company ends a partnership with another entity |
expands_facilities | Company expands physical facilities |
expands_offices_in | Company expands offices in existing location |
expands_offices_to | Company opens offices in new location |
files_suit_against | Company files lawsuit against another entity |
goes_public | Company IPO or public listing |
has_earnings | Company reports earnings results |
has_issues_with | Company experiences issues (security, product, etc.) |
has_revenue | Company reports revenue figures |
has_valuation | Company receives a valuation or valuation change |
hires | Company hires new executive or key person |
identified_as_competitor_of | Company identified as competitor to another |
increases_headcount_by | Company grows workforce |
integrates_with | Company announces integration with another product |
invests_into | Company makes investment into another company |
invests_into_assets | Company invests in assets (real estate, equipment) |
is_developing | Company developing new product or technology |
launches | Company launches new product or service |
leaves | Executive or key person leaves the company |
loses_client | Company loses a customer or client relationship |
merges_with | Company merges with another company |
opens_new_location | Company opens new physical location |
partners_with | Company announces partnership |
promotes | Company promotes employee to new role |
rebrands_to | Company rebrands or changes its name |
receives_award | Company receives industry award or recognition |
receives_financing | Company receives financing (Series A, B, C, debt, etc.) |
recognized_as | Company recognized for achievement |
retires_from | Executive retires from the company |
sells_assets_to | Company sells assets to another entity |
signs_new_client | Company announces new customer win |
spins_off_company | Company spins off a subsidiary |
spins_off_division | Company spins off a division or business unit |
splits_into | Company splits into multiple entities |
Signal Categories
| Category | Description |
|---|---|
strategic | M&A, partnerships, divestitures, rebrands |
financial | Funding, revenue, earnings, valuations, IPOs |
leadership | Hires, promotions, departures, retirements |
workforce | Headcount changes (growth and reduction) |
operations | Facility expansions, office moves, closures |
technology | Product launches, integrations, R&D |
competitive | Competitor identification, client wins/losses |
market | Events, awards, recognition |
risk | Bankruptcy, lawsuits, security issues |
revenue | Client wins, client losses |
Example Signal
What a single entry looks like in a delivered signal file:
{
"signal_id": "a7d3e1f2-5b84-4c9a-b6e2-9f1a8c3d7e04",
"batch_id": "2026-04-15-00-00-00",
"signal_type": "news",
"signal_subtype": "receives_financing",
"detected_at": "2026-04-14T09:15:00Z",
"association": "company",
"company": {
"name": "Vanta",
"domain": "vanta.com", // match on domain
"linkedin_url": "linkedin.com/company/vanta", // or match on LinkedIn URL
"industries": ["Software Development", "Cybersecurity"],
"employee_count_low": 501,
"employee_count_high": 1000
},
"contact": [],
"data": {
"title": "Vanta raises $150M Series C to expand automated compliance platform",
"summary": "Vanta closed $150M Series C led by Craft Ventures at $2.5B valuation on Apr 14th '26.",
"article_sentence": "Vanta, the automated security and compliance platform, has closed a $150 million Series C round led by Craft Ventures, bringing its valuation to $2.5 billion.",
"body": "Vanta raises $150M Series C at $2.5B valuation. The funding will accelerate expansion into enterprise compliance automation...",
"author": "Connie Loizos",
"category": "receives_financing",
"confidence": 0.97, // 0.0-1.0; how certain this event was correctly identified
"financing_type": "Series C",
"financing_type_normalized": "Series C",
"financing_type_tags": ["equity"],
"amount": "$150M",
"amount_normalized": 150000000,
"effective_date": "2026-04-14",
"found_at": "2026-04-14T09:15:00Z",
"published_at": "2026-04-14T08:00:00Z",
"planning": false,
"location_data": [
{"city": "San Francisco", "state": "California", "country": "US", "continent": "North America"}
],
"product_data": {
"name": "Vanta Trust Center",
"full_text": null,
"release_type": null,
"release_version": null,
"fuzzy_match": null
},
"product_tags": ["security", "compliance"],
"job_title_tags": [],
"assets_tags": [],
"image_url": "https://techcrunch.com/wp-content/uploads/2026/04/vanta-series-c.jpg",
"url": "https://techcrunch.com/2026/04/14/vanta-raises-150m-series-c/"
}
}Field Reference
Standard envelope and entity fields are shared across all signals — see Schema and Resolution. The fields below are specific to this signal:
Signal-Specific Fields
The data object contains everything unique to this signal type — the intelligence extracted from the news article.
| Field | Type | Description |
|---|---|---|
title | string | Article headline as published by the source. Useful for display in notifications or activity feeds |
summary | string | One-line headline describing the event. Designed to be shown directly to end users as a notification or list item. Typically 10–20 words, always includes the company name and event details |
article_sentence | string | Key sentence from the source article that best captures the event. Useful for displaying as proof or quick context to end users |
body | string | Full article body text. Contains the complete content of the source article. Useful for deeper analysis, keyword extraction, or full-context display |
author | string | Article author name. Useful for attribution or tracking specific journalist coverage |
category | string | Category of the news event, aligning with subtypes (e.g., receives_financing, acquires). Useful for routing signals to different sales motions |
confidence | float (0.0–1.0) | How certain the classification model is that this event was correctly identified and categorized. Higher values mean the article explicitly describes the event. Lower values indicate indirect or ambiguous mentions. Useful for filtering in production — recommended threshold: 0.85+ for high-precision use cases |
financing_type | string | Raw financing round type as reported (e.g., "Series A", "Seed", "debt", "grant"). Present when signal_subtype is receives_financing, invests_into, or goes_public |
financing_type_normalized | string | Standardized version of financing_type for consistent filtering across articles that describe the same round differently |
financing_type_tags | array[string] | Types of financing involved: angel, debt, donation, equity, grant, ipo, seed. Present when signal_subtype is receives_financing |
amount | string | Funding amount as reported in the article (e.g., "$150M", "$2.5B"). Present on financing-related subtypes |
amount_normalized | integer | Funding amount normalized to USD integer (e.g., 150000000). Useful for filtering and sorting by deal size |
effective_date | string (date) | Date the event took effect. May differ from publication date for pre-announced events |
found_at | string (ISO 8601) | When the article was discovered by our crawler. Useful for tracking pipeline latency |
published_at | string (ISO 8601) | Article publication date. Useful for recency filtering and outreach timing |
planning | boolean | Whether this is a planned/future event vs. one that already occurred. Useful for distinguishing "Company plans to expand" from "Company expanded" |
contact | string | Contact person mentioned in the article. Present on hires, leaves, promotes, and retires_from subtypes |
job_title | string | Job title mentioned in the context of the event. Present on hires, promotes, and leaves subtypes |
job_title_tags | array[string] | Job function categories for hire/promotion events (e.g., c_suite, vp, director). Useful for filtering leadership signals |
headcount | integer | Headcount number mentioned in the event. Present on increases_headcount_by and decreases_headcount_by subtypes |
location | string | Location string associated with the event (raw text). Present on expansion and office-related subtypes |
location_data | array[object] | Structured location data. Each object contains: city, state, country, region, continent, zip_code (string), and fuzzy_match (boolean). Present when a geographic location is mentioned in the article |
product_data | object | Structured product data. Present on launches and is_developing subtypes |
product_data.name | string | Product name |
product_data.full_text | string | Full text context where the product was mentioned |
product_data.release_type | string | Type of release (e.g., "major", "minor", "beta") |
product_data.release_version | string | Version string for the release |
product_data.fuzzy_match | boolean | Whether the product name was matched via fuzzy matching |
product_tags | array[string] | Product category tags (e.g., ai_ml, saas, fintech). Useful for building tech-category targeting |
assets_tags | array[string] | Asset category tags. Present on acquires, sells_assets_to, and invests_into_assets subtypes |
assets | string | Assets involved in the transaction. Present on acquisition and divestiture subtypes |
event | string | Event name. Present on attends_event subtype |
award | string | Award name. Present on receives_award subtype |
recognition | string | Recognition details. Present on recognized_as subtype |
vulnerability | string | Security vulnerability mentioned. Present on has_issues_with subtype |
image_url | string (URL) | Article thumbnail/header image URL. Useful for rich display in notifications |
url | string (URL) | Source article URL. Useful for linking users to the original coverage |
Timing & Delivery
detected_atis when we discovered and processed the article. Usepublished_atfor the original publication date andeffective_datefor when the event itself occurred.- One signal per subtype per company per 7-day window. If the same event is covered by multiple outlets, we deduplicate to a single signal using the earliest article discovered.
- Each delivery arrives in a timestamped folder. Treat all signals in a new folder as recent — no need to diff against prior deliveries.
Coverage
- Refresh: Weekly
- Coverage: 4,000,000+ companies monitored
- Best for: SDR/AE outreach timing, ABM triggers, competitive intelligence, funding-based prospecting
Updated 9 days ago