Startup Funding Rounds Tracker: Recently Funded Companies

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Track funding rounds for companies at every stage, from pre-seed through growth. Each record has the company, amount, round, date, and investors. Every round is matched across the outlets that reported it and resolved to one canonical company, so you get one row per round instead of one per article. Set your filters, run it, and pay only for the records you get back. No API key, no signup, no sales call.

Use it for funding rounds data, company funding API, funding tracker, recently funded companies, new funding announcements, venture funding data, startup funding monitor, investment rounds, Series A B C data.

What you get

Every record carries all of the below. The table view shows the columns that scan best; the full record is in the JSON, CSV, and Excel exports.

• Company. name, domain, description, LinkedIn URL and handle, HQ city and country, industry group, industry sub-tags, verticals, employee count, founded year, and business model.
• Round. stage, amount in USD, the original currency and amount as reported, announced date, and the date we first saw it.
• Investors. every investor named in the round, each with a stable id you can join on.
• Corroboration. how many independent reports back the round, so one confirmed by six outlets reads differently from one a single blog mentioned.

Results export to JSON, CSV, or Excel, or stream straight to your database via the Apify API.

Common use cases

• Sales and prospecting. Find accounts that just raised, and reach them while the news is fresh.
• Market research. Track funding rounds by industry, country, and date.
• Data enrichment. Add funding rounds to your CRM or warehouse.
• Deal sourcing. Scan new activity, for investors and corp dev teams.

Filters

Input	Description
maxItems	Max records (default 100)
cursor	Advanced: resume from a previous run's NEXT_CURSOR to paginate ahead
since	Only records on or after this date (YYYY-MM-DD), e.g. 2026-01-01. ISO-8601 timestamps also work.
round	Filter by funding round. Leave empty to get every round, including deals where the stage was not disclosed. If you do pick rounds, add "Not disclosed" to keep those deals in. Allowed values: pre-seed, seed, angel, series-a, series-b, series-c, series-d, series-e, series-f, series-g, series-h, growth, extension, bridge, convertible, debt, grant, other, unknown, series-i, safe, pre-ipo, secondary, pipe.
industryGroup	Filter by industry group (LinkedIn-style industry labels, exact match). Pick "unknown" for companies with no industry on record. They are excluded from any other industry filter.
industryGroups	Filter by industry group (LinkedIn-style labels, exact match). Select several to cover related industries in one run. About a fifth of companies have no industry on record, so add "unknown" to keep those deals in.
naicsCode	Filter by NAICS 2022 code. Matches the code and everything beneath it, so picking a sector like Manufacturing (31-33) returns every manufacturer under it. Pick "Not classified" for companies we could not classify.
verticals	Filter by high-level sector (AI, fintech, climate, etc.). Broader than industry group; matches any company mapped to the selected vertical. Pick "unknown" for companies with no sector on record. They are excluded from any other sector filter.
minAmountUsd	Minimum amount in USD.
maxAmountUsd	Maximum amount in USD.
country	Filter by company HQ country. Pick "Not disclosed" for companies whose HQ country we never established. They are excluded from any other country filter.
countries	Filter by company HQ country. Select several to cover a whole region in one run instead of one run per country. About a quarter of companies have no HQ country on record, so add "Not disclosed" to keep those deals in.
employeeBuckets	Filter by company size. Select one or more bands.

Leave everything empty to get the newest records first, or narrow by the filters above. Each run saves a NEXT_CURSOR for pagination.

Example output

{
  "id": "019fdde2-30c8-7eda-bcb5-42b3d5ef9516",
  "company": {
    "id": "019df869-7f8d-7c56-aecc-9d08c84ccdac",
    "name": "Whatnot",
    "domain": "whatnot.com",
    "description": "Whatnot - The Live Shopping Marketplace. Shop, sell, and connect around things you love.",
    "linkedinHandle": "company/whatnot-inc",
    "linkedinUrl": "https://www.linkedin.com/company/whatnot-inc",
    "linkedinGeoId": "103644278",
    "linkedinIndustryId": "1285",
    "hqCity": "Marina Del Rey",
    "hqCountry": {
      "code": "US",
      "name": "United States"
    },
    "industryGroup": "Internet Marketplace Platforms",
    "naicsCode": "44-45",
    "naicsLevel": 2,
    "industrySubTags": [
      "live-shopping",
      "auctions",
      "marketplace",
      "collectibles"
    ],
    "verticals": [
      "commerce"
    ],
    "employeeCountBucket": "1001-5000",
    "foundedYear": 2019,
    "businessModel": "marketplace"
  },
  "round": "series-g",
  "amountUsdCents": 54500000000,
  "amountUsd": 545000000,
  "amountOriginalCurrency": "USD",
  "amountOriginalCents": 54500000000,
  "investors": [
    {
      "id": "019faf77-53ff-7ce9-8e8c-0432bd49b754",
      "name": "Alphabet CapitalG"
    },
    {
      "id": "019df8b0-f848-722f-9658-5cea256e0e0a",
      "name": "Andreessen Horowitz"
    },
    {
      "id": "019e2b1d-82d8-7276-b7b9-36cebf849155",
      "name": "Bond"
    },
    {
      "id": "019df8b1-2b91-7e3f-97a0-6b54e0e8fad7",
      "name": "Y Combinator"
    }
  ],
  "announcedAt": "2026-08-07",
  "discoveredAt": "2026-08-07T20:20:16.158Z"
}

FAQ

What data does this actor return?

Track funding rounds for companies at every stage, from pre-seed through growth. Each record has the company, amount, round, date, and investors. Fields: Company, Domain, Round, Amount (USD), Announced, Country, City, Industry, NAICS, Employees, LinkedIn. Each one is matched to a canonical company.

Is this a Crunchbase, PitchBook, or Coresignal alternative?

Yes. It is a self-serve, API-first alternative to Crunchbase, PitchBook, Coresignal, and Harmonic. You pay per result, with no annual contract and no sales call.

How fresh is the data?

Most records are available the same day they are announced. Across the last 30 days, the median gap between a public announcement and the record being available was under one day.

Can I monitor funding rounds on a schedule?

Yes. Save your filters as a task and use Apify's scheduler to run it daily or weekly. Each run stores a NEXT_CURSOR. Pass it to the next run to pick up where the last one stopped, so you only pay for records you have not seen yet.

Some records have an empty field. Can I still get those?

Yes. Not every announcement states every detail, and where a value was never disclosed the field is left empty rather than guessed. Filters that can be empty offer a Not disclosed option (HQ country and industry, plus funding round where it applies). Select it to include those records instead of dropping them from a filtered run.

How is the data deduplicated?

Each real-world event is matched across every outlet that reported it and resolved to one canonical company (and investors), so you never get the same round or deal twice.

How do I get the next batch of records?

Each run saves a NEXT_CURSOR to its key-value store. Pass it as the cursor input on the next run to continue where you left off. For new records over time, use the since filter.

Is there a free way to try it?

Yes. Run it here and pay only for the records you get back, or go direct at datahyena.com with 50 free credits.

Can I get this data over an API instead?

Yes. Datahyena is API-first: REST, webhooks, or MCP (Claude, Cursor, Codex). This actor is the Apify-native way to run it.

Use it in your own stack

For ongoing use it is cheaper and more flexible to go direct: REST, webhooks, and MCP, with subscription pricing and 50 free credits to start.

datahyena.com · Docs · MCP

Terms of use

Records returned by this Actor are licensed for use inside your own products and workflows. Building on the data is encouraged. Reselling, redistributing or republishing the records as data, in raw or substantially raw form, is not permitted, and neither is systematic extraction to reconstruct the dataset.

Full terms: datahyena.com/terms

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