Recently Funded Startups Database (Instant)

Recently Funded Startup Database

(instantly query a prebuilt database of startups that raised funding from January 2025 onward)

This Actor does not scrape anything when you run it. Every company was collected, verified, and enriched in advance. You pick your filters, and matching companies are returned in seconds.

Results are available as JSON, CSV, or Excel.

What's in the database

Over 13,000 companies that raised funding from 1 January 2025 onward. Updated monthly; because every record is verified in advance, the newest rounds run a few weeks behind today's date.

• By headquarters region — the United States and Europe together make up the large majority of the database. Canada, Asia, Oceania, Latin America, Africa, and the Caribbean are all included, but hold far fewer companies.
• By quarter — every quarter from 2025-Q1 onward is covered. The most recent quarter is always partial, since it runs up to the last collection date.
• Largest industries — Healthcare & Medical Devices, Fintech, Enterprise Software (SaaS), AI & Machine Learning, Climate & Energy, and Biotech & Pharmaceuticals.

Tip: leave a filter empty to include everything in it. Filters combine, so picking two industries, two regions, and two quarters returns companies matching any of those industries, in any of those regions, in any of those quarters.

What you get

Not every field is filled for every company. Nothing is inferred or estimated, so a field is empty whenever it could not be verified. The labels below are honest about how often each one arrives.

On every company:

• companyName - the company's trading name.
• website - its verified homepage. Every website was individually checked against corroborating evidence for that specific company — not guessed from a name match.
• domain - the registrable domain, handy for deduplication and CRM matching.
• industry - exactly one label from a closed 23-value list, so filtering is consistent.
• region - headquarters region: United States, Europe, Canada, Asia, Africa, Oceania, Latin America, or Caribbean. Regions never overlap: Asia includes the Middle East, Africa includes North Africa.
• fundingDate, fundingQuarter - when the round was announced or filed.

On almost every company:

• country - headquarters country.
• moneyType - Equity, Debt, SAFE, and similar, taken from the source rather than inferred.

On most companies (roughly seven in ten or more):

• fundingAmount - the raised amount with its currency symbol ($8,397,541, €1,300,000), where it was disclosed. Text, not a number, so the symbol travels with the value.
• city - headquarters city.
• description - what the company actually does, taken from its own website where possible.
• contact1Name, contact1Title - the best-evidenced named person with a published role, such as founder, CEO, or another senior leader.

On about half:

• linkedInCompany - the official company profile.
• addressLine, state - street-level location. Heavily US-weighted: nearly every US company has one, while European and other non-US companies usually do not.
• phone - a verified contact number for the company.
• contact2Name, contact2Title - a second named person.

On fewer than half:

• email, emailsAll - contact addresses published on the company's own site.
• fundingStage - Pre-Seed, Seed, Series A/B/C, or Growth/Late, only where it was stated.
• contact3Name, contact3Title - a third named person.

Rarely present — do not plan around these:

• twitter - only about a quarter of companies list one.
• contact1LinkedIn, contact2LinkedIn, contact3LinkedIn - personal LinkedIn URLs are present on only a small percentage of records. Contact names and titles are far better covered than their LinkedIn links.

One company ships per domain, so you never get the same business twice.

Sample output (CSV-Friendly Flattened JSON)

This is a well-filled record, shown to illustrate the full shape. A typical company has fewer fields populated — see the coverage labels above.

{
    "companyName": "Lucem Health",
    "website": "https://lucemhealth.com/",
    "domain": "lucemhealth.com",
    "industry": "AI & Machine Learning",
    "description": "Lucem Health develops practical AI tools that help healthcare providers accelerate disease detection and treatment.",
    "region": "United States",
    "country": "United States",
    "state": "North Carolina",
    "city": "Davidson",
    "addressLine": "210 Delburg St., Davidson, NC 28036",
    "fundingDate": "2026-03-26",
    "fundingQuarter": "2026-Q1",
    "fundingAmount": "$8,397,541",
    "fundingStage": "Series A",
    "moneyType": "Equity",
    "email": "info@lucemhealth.com",
    "emailsAll": ["info@lucemhealth.com"],
    "phone": "919.371.6323 x703",
    "linkedInCompany": "https://www.linkedin.com/company/lucem-health",
    "twitter": "https://twitter.com/lucemhealth",
    "contact1Name": "Sean Cassidy",
    "contact1Title": "CEO",
    "contact2Name": "Eric Navarro",
    "contact2Title": "CTO",
    "contact3Name": "Conrad Gudmundson",
    "contact3Title": "Chief Commercial Officer"
}

Typical use cases

• Lead generation — build a target list of recently funded companies in your industry and market.
• Market research — track which sectors and regions are raising, quarter by quarter.
• Investor and competitor tracking — see who raised, when, and at what stage.
• Recruiting — find newly funded companies that are about to start hiring.

Quick start

1. Pick one or more industries (or leave empty for all).
2. Pick one or more regions (or leave empty for all).
3. Pick one or more funding quarters (or leave empty for all).
4. Set maximum results, click Start, and download your data in JSON, CSV, or Excel format.

FAQ

How fresh is the data? The database covers funding announced from 1 January 2025 onward and is updated once a month. Because collection, verification, and enrichment all happen before you run it, the newest rounds are typically a few weeks behind today's date — that lag is what buys you verified websites, working contacts, and no scraping wait at query time. The most recent quarter available is always partial, since it runs up to the last collection date.

Which regions are best covered? The United States and Europe together account for the large majority of the database. Canada, Asia, Africa, Oceania, Latin America, and the Caribbean are included but hold fewer companies, so narrow filters on those regions may return few or no results.

Why are some fields empty? Because the value could not be verified. Amounts and stages are only included when they were actually disclosed — most companies have a disclosed amount, but a stated stage is present on fewer than half. Contact details follow the same rule: every company has a verified website, while phone numbers sit around half, email addresses under half, and personal LinkedIn URLs on only a small percentage. Nothing is inferred or estimated — an honest empty field is better than a fabricated one. See "What you get" above for the per-field breakdown before you build a workflow on any single column.

Are addresses available outside the United States? Often not. Street-level detail is much more consistently available for US companies, so US coverage is near-complete while European and other non-US companies frequently have only country and city. Region, country, and city are the location fields to rely on globally.

Why does my query return nothing? Combining several narrow filters can produce an empty result — for example, one small industry in a thinly covered region in a single quarter. Widen any one of the three filters. A run that returns no companies costs you nothing, since you are only charged per company returned.

Are the websites reliable? Every website was verified individually against hard corroborating evidence tied to that specific company, never a name match alone. Where no solid evidence existed, the company was left out rather than shipped with a guess.

What if something looks wrong? Please open an issue on this Actor's page first — that is the fastest way to get it looked at. You can also reach out at southdionysus@gmail.com.

Start with a broad query to see the shape of the data, then narrow it down.

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This Actor is an independent tool. It is not affiliated with, endorsed by, or connected to any of the companies listed in the dataset.