Startup Investors Database - 10,469 VC, Angel, PE & Accelerator Firms

Search a curated database of 10,469 venture capital, angel, private equity, and accelerator firms with verified investor contacts. The most comprehensive startup investor database for fundraising, lead generation, and VC market research. Filter by firm type, focus area (AI, biotech, fintech, etc.), investment stage, and country. Pay per firm or contact returned - no flat fee. Export JSON, CSV, or Excel; integrate via API or Apify MCP.

Apify Store: https://apify.com/johnvc/startup-investors-data-scraper Example code: https://github.com/johnisanerd/Apify-Startup-Investors-Data-Scraper

What this returns

For each investor firm:

• Identity - firm name, type (VC, Angel, PE, Accelerator, Family Office, etc.), description, AUM
• Location - full address, city, state, country, ZIP, phone
• Web presence - website, LinkedIn, Crunchbase, Twitter (X), Facebook
• Investment profile - stages (Seed → Late Stage), focus areas, industries
• Provenance - created_at, updated_at, last_checked timestamps
• Investor contacts (optional) - partners, principals, and associates with name, job title, email, LinkedIn, location, headline, areas of interest, portfolio companies, and minimum/maximum/target check size

Use cases

• Startup fundraising - Find VC, angel, and PE firms aligned with your industry and stage. Build a targeted investor outreach list with verified partner contacts.
• B2B sales to VCs and portfolio companies - Identify decision-makers at investment firms. Build prospect lists for fund-services, legal, audit, and SaaS sales.
• Financial research & analysis - Map investment trends across industries. Profile investor behavior and stage preferences.
• Business development - Source advisors, board members, and partnership opportunities from a pool of 10,000+ firms.

Quickstart

1. Open the actor: https://apify.com/johnvc/startup-investors-data-scraper
2. Paste this input and click Start:

{
  "Firm_Types": ["Venture Capital Investor"],
  "Focus_Areas": ["Artificial Intelligence"],
  "Countries": ["United States"],
  "Max_Results": 25,
  "Include_Contacts": true
}

3. Open the Output tab. Switch between Overview, Full Firm Detail, and Firms with Contacts views. Export to JSON, CSV, or Excel.

Input parameters

Parameter	Type	Required	Default	Description
Firm_Types	array	❌	["Venture Capital Investor"]	Filter by firm type. See valid values below.
Focus_Areas	array	❌	["Artificial Intelligence"]	Filter by industry / focus area. See valid values below.
Investment_Stages	array	❌	["Seed", "Series A"]	Filter by stage. Recommended values: Pre-Seed, Seed, Series A, Series B, Series C, Series D, Late Stage, Growth, Private Equity, Mezzanine, IPO, Debt.
Countries	array	❌	["United States"]	Filter by HQ country. Use full English names.
Keyword	string	❌	"Sequoia"	Search across firm name, description, and other text fields.
Max_Results	integer	❌	100	Maximum firms to return. Range: 1–10000.
Offset	integer	❌	0	Skip this many firms before returning. Use with Max_Results to paginate across multiple runs.
Order_By	enum	❌	created_at	One of: created_at, firm_name, firm_country, firm_type_id.
Order_Direction	enum	❌	desc	asc or desc.
Include_Contacts	boolean	❌	false	Include investor_contacts array on each firm.

All parameters are optional - omit everything to browse the full database.

Valid Firm Types

Angel Investor, Accelerator, Corporate Venture Capital Investor, Economic Development Organization, Hedge Fund, Incubator, Multi Family Office, Merchant Bank, Other, Private Equity, Real Estate, Single Family Office, Secondary, Startup, Tech Transfer Office, Venture Capital Investor, Venture Debt

Valid Focus Areas

Administrative, Advertising, Agriculture and Food, Apps, Artificial Intelligence, Biotechnology, Blockchain & Crypto, Clothing and Apparel, Commerce and Shopping, Community and Lifestyle, Consumer Electronics, Consumer Goods, Content and Publishing, Data and Analytics, Design, Education, Energy, Events, Financial Services, Food and Beverage, Gaming, Government, Hardware, Health Care, Information Technology, Internet Services, Lending and Investments, Manufacturing, Media and Entertainment, Messaging and Communication, Mobile, Music and Audio, Natural Resources, Navigation and Mapping, Other, Payments, Platforms, Privacy and Security, Professional Services, Real Estate, Sales and Marketing, Science and Engineering, Software, Sports, Sustainability, Transportation, Travel and Tourism, Video, Uncategorized

Example output

A firm record (one row in the dataset):

{
  "firm_id": 11407,
  "firm_type_id": "AC",
  "firm_type_name": "Accelerator",
  "firm_name": "PALM VENTURES",
  "firm_description": "PALM VENTURES is an active family-office investment company that partners with management teams to build substantial value and create positive social impact. They invest across the spectrum from incubation to growth equity, buyouts, and distressed small public companies.",
  "firm_city": "Greenwich",
  "firm_state": "CT",
  "firm_country": "United States",
  "firm_website": "https://www.palmventures.com",
  "firm_linkedin_url": "https://www.linkedin.com/company/palmventuresco",
  "crunchbase_url": "https://www.crunchbase.com/organization/palm-ventures",
  "firm_stages": ["Seed", "Late Stage", "Private Equity"],
  "firm_aum": 0.0,
  "firm_focus": ["Financial Services", "Information Technology", "Consumer Products & Services"],
  "industry_names": ["Financial Services", "Information Technology"],
  "last_checked": "2025-06-07T11:34:31.982308+00:00",
  "created_at": "2025-06-12T07:51:12.827480+00:00",
  "updated_at": "2025-06-12T07:51:12.827480+00:00",
  "investor_contacts": [
    {
      "name": "Brad Higgins",
      "first_name": "Brad",
      "last_name": "Higgins",
      "job_title": "Managing Partner",
      "title": "Managing Partner",
      "email": "brad@palmventures.com",
      "linkedin_url": "https://www.linkedin.com/in/bradhiggins",
      "location_city": "Greenwich",
      "location_country": "United States",
      "headline": "Managing Partner at Palm Ventures",
      "areas_of_interest_names": ["Financial Services", "Information Technology"],
      "min_investment": 250000,
      "max_investment": 5000000,
      "target_investment": 1000000,
      "firm_name": "PALM VENTURES"
    }
  ],
  "search_metadata": {
    "focus_areas": ["Artificial Intelligence"],
    "max_results": 25,
    "order_by": "created_at",
    "order_direction": "desc",
    "include_contacts": true,
    "search_timestamp": "2026-05-10T15:31:46.941141",
    "total_results_found": 25,
    "query_execution_time": 5.586141
  }
}

Note on title vs job_title: every contact emits both title and job_title with the same value. job_title is the canonical field going forward; title is kept temporarily for backwards compatibility and will be removed in a future release. Migrate your downstream code to job_title.

Pricing

Pay-per-event - you only pay for what you receive.

Event	Price	When charged
Setup	$0.01	Once per actor run
Firm Returned	$0.04	Per investor firm in the result set
Contact Returned	$0.02	Per investor contact (only when Include_Contacts: true)

Worked example. A run that returns 10 firms with 2 contacts per firm costs:

$0.01 (setup) + 10 × $0.04 (firms) + 20 × $0.02 (contacts) = $0.81

A bare firm list (no contacts) of 100 firms costs $0.01 + 100 × $0.04 = $4.01.

If your Apify budget is below the estimated cost of a run, the actor logs a friendly warning, charges only the setup fee, and exits gracefully.

FAQ / Troubleshooting

Q: I got 0 results. A: Your filter combination may be too narrow. Try broadening: drop Investment_Stages or Countries, or remove Focus_Areas to see what's available. The Keyword filter is OR'd with name/description matches, so a very specific keyword may eliminate everything.

Q: How fresh is the data? A: Each firm has a last_checked timestamp showing when it was last verified. The database is refreshed continuously; most records are checked within the last 6 months.

Q: Why is firm_aum zero for so many firms? A: AUM is only included when the firm publicly discloses it. A 0.0 value means we don't have a disclosed figure, not that the firm has no AUM.

Q: Some contacts have email: null. Why? A: Email coverage varies by firm. We only include emails we have verified. LinkedIn URLs are present for ~95% of contacts and are the recommended outreach channel when email is missing.

Q: How do I filter by stage when my stage isn't in the recommended list? A: Investment_Stages accepts any string value - the filter is matched against the database. Stick to the recommended list for the best hit rate; obscure values may match few or zero firms.

Q: How do I fetch a large result set, or split a big query across multiple runs? A: Use Offset for pagination. Set Max_Results=1000, Offset=0 for the first run, Offset=1000 for the second, Offset=2000 for the third, and so on. The search_metadata.offset field in each output confirms the page position. For gap-free pagination, sort on a unique field: set Order_By: "firm_name". Paging on the default created_at can occasionally skip or repeat a firm when several firms share the same timestamp.

Q: My actor run failed with a budget warning. What now? A: Increase your run budget in the Apify Console under the run's settings, or lower Max_Results to fit the budget. The setup fee is small ($0.01) so re-running costs almost nothing.

Q: Can I use this from Claude, Cursor, or another MCP-aware client? A: Yes - connect to the Apify MCP server and search for "venture capital" or "startup investors". This actor exposes its full input schema to the LLM. See the MCP integration docs.

🔌 Integrations: Keep Your Investor Database Fresh

One run answers one question ("who backs seed-stage AI in the US?"). The value compounds when you run it on a cadence, so new firms and refreshed partner contacts land in your CRM instead of a stale spreadsheet. That is the practical difference between a static export and a living investor database. See the full list of Apify platform integrations.

Tasks and Schedules (the core recipe). Save one task per list you maintain (seed AI in the US, European fintech, family offices), then attach a schedule from the actor's Actions, then Schedule menu. Because Order_By and Offset are stable, a scheduled run reproduces the same slice of the database and picks up firms added since last time. Useful cron strings:

Cron	Cadence	Good for
0 6 * * 1	Mondays, 6 AM UTC	Weekly refresh of an active raise target list
0 3 1 * *	1st of the month, 3 AM UTC	Monthly rebuild of a full sector or country list
0 6 * * *	Daily, 6 AM UTC	High-churn prospecting, sales into VC firms
0 4 1 */3 *	Quarterly, 1st at 4 AM UTC	Slow-moving segments such as Venture Debt or family offices

Compare updated_at and last_checked across runs to see which firms actually changed. One schedule can trigger several tasks at once.

n8n. This API ships an n8n community node, n8n-nodes-startup-investors-api. In n8n: Settings, then Community Nodes, then install n8n-nodes-startup-investors-api. A four-step outreach pipeline: Schedule Trigger, then the Startup Investors API node with Include_Contacts on, then a Filter on firm_stages containing Series A, then HubSpot, Airtable, or Google Sheets. The node also works as an AI Agent tool.

Make and Zapier. The same pattern works no-code with Make and Zapier: trigger on a schedule, run the actor, route each firm row into your CRM, a Slack channel, or a sheet.

MCP and AI agents. Add this actor as a tool through the Apify MCP server and an agent can query the investor database in plain language ("pre-seed fintech investors in Germany, with partner contacts"). Works from Claude Code (free trial), Claude Cowork (free trial), Cursor, VS Code, Cline, and Windsurf. The agent picks the filters; you still pay only for the firms it returns.

Webhooks. For anything custom, fire an Apify webhook on ACTOR.RUN.SUCCEEDED to push each run's dataset into your own service the moment it finishes.

Store the history. Write every run into a table so you accumulate a private, versioned investor database instead of re-querying from zero. This is where the actor earns its keep as a Crunchbase alternative: you own the rows, and you pay per firm rather than per seat.

from apify_client import ApifyClient

client = ApifyClient("YOUR_APIFY_TOKEN")

run = client.actor("johnvc/startup-investors-data-scraper").call(run_input={
    "Firm_Types": ["Venture Capital Investor", "Angel Investor"],
    "Investment_Stages": ["Seed", "Series A"],
    "Countries": ["United States"],
    "Include_Contacts": True,
    "Order_By": "firm_name",
    "Max_Results": 500,
})

for firm in client.dataset(run.default_dataset_id).iterate_items():
    print(firm["firm_name"], firm["firm_country"], firm["firm_stages"], firm["updated_at"])
    for contact in firm.get("investor_contacts", []):
        print("  ", contact["name"], contact["job_title"], contact.get("email"), contact.get("linkedin_url"))

Pin apify-client>=3,<4. On version 3 the run object is typed, so it is run.default_dataset_id, not a dictionary key. Upsert on firm_id to dedupe across scheduled runs.

Support

For technical support, feature requests, or feedback, drop a note via the actor's store page.

---

n8n integration

Available as an n8n community node, n8n-nodes-startup-investors-api. In n8n: Settings, Community Nodes, install n8n-nodes-startup-investors-api, then use it in any workflow (it also works as an AI Agent tool).

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Featured Tasks

Ready-to-run examples that show this API solving a specific problem. Each opens its own setup so you can run it on your account in one click.

• Find seed-stage SaaS investors in the US - US venture firms backing seed-stage software, with website, focus areas, and AUM.
• Build a list of European fintech VCs with contacts - fintech-focused European firms with partner names, titles, and LinkedIn URLs included.
• Target healthcare angel investors for a Series A - angel firms active in health care, filtered to Series A participation.
• Find Corporate Venture Capital Firms with Contacts - corporate venture arms with partner names, job titles, emails when available, and LinkedIn.
• Find Venture Debt Firms for Non-Dilutive Funding - venture debt providers with type, city, country, website, focus areas, and investment stages.

🔗 Related Tools

Building an investor database pipeline? These pair well with the firm and contact records this API returns:

• Crunchbase Company API: funding rounds and firmographics for the companies a firm has backed. Every record here already carries a crunchbase_url, so the join is free.
• PitchBook Company API: private company and round data when you need the company side of a deal, not the investor side.
• LinkedIn Profile API: enrich the partners in investor_contacts before outreach. Roughly 95% of contacts arrive with a linkedin_url.
• LinkedIn Company API: headcount, industry, and firmographics for the firm itself, joined on firm_linkedin_url.
• Investment Finance Professionals: contacts at SEC-registered investment advisers, a different slice of the capital market than VC and PE.

Alternatives exist. Angel Investor Contact Finder covers the angel slice and shows about 17 users and no public reviews at the time of writing. This API covers 10,469 firms across 17 firm types (venture capital, angel, private equity, accelerator, incubator, corporate VC, family office, venture debt, hedge fund, and more), with stage and country filters, partner contacts on request, and pay-per-record billing.

❓ More questions about the investor database

What is the best investor database for a startup raise?

It depends on what you need to walk away with. This one is a searchable investor database of 10,469 firms covering venture capital, angel, private equity, accelerator, incubator, corporate VC, family office, and venture debt. You filter on Firm_Types, Focus_Areas, Investment_Stages, and Countries, and you pay per firm returned instead of buying a seat. Set Include_Contacts: true and each firm arrives with its partners attached: job_title, linkedin_url, email where verified, and min, max, and target check size.

Is this a good Crunchbase alternative for investor data?

For the investor side of the market, yes. You get firm profiles, focus areas, stages, AUM where it is disclosed, websites, and partner contacts, and every record carries a crunchbase_url so you can join back to whatever you already have. It is not a round-by-round company funding graph; if that is what you need, pair it with the Crunchbase Company API. The practical difference is billing: a few cents per record, no annual seat.

What is a good PitchBook alternative for a venture capital database?

If your job is to build a target list of firms rather than to diligence a single company, this venture capital database gets you there for the cost of the rows you keep. Filter to the firms you care about, export JSON, CSV, or Excel, and stop. For company-level profiles and rounds, the PitchBook Company API is the companion tool.

How do I find pre-seed investors for my startup?

Filter on the stage, then narrow by sector and geography. Pre-seed investors write the first institutional check, so most of them are angels, micro-VCs, and accelerators rather than large funds:

{
  "Investment_Stages": ["Pre-Seed"],
  "Focus_Areas": ["Artificial Intelligence"],
  "Countries": ["United States"],
  "Include_Contacts": true,
  "Max_Results": 100
}

Each row comes back with firm_name, firm_website, firm_stages, and the partners who actually take the meeting.

How do I build a private equity firms list?

Set Firm_Types: ["Private Equity"] and leave the rest open, or add Countries to scope it. Add "Order_By": "firm_name" and page with Offset if you want the whole set in a stable order. Private equity firms in this database carry the same fields as the VC records: description, AUM where disclosed, website, LinkedIn, stages, and focus areas.

How do I find and contact family office investors?

Family office investors are the hardest group to reach because most do not publish a partner directory. Query both office types and turn contacts on:

{
  "Firm_Types": ["Single Family Office", "Multi Family Office"],
  "Include_Contacts": true,
  "Max_Results": 50
}

A family office manages the wealth of one household or a handful of them, so check sizes vary far more than they do at a fund. The min_investment, max_investment, and target_investment fields on each contact tell you whether your round is even in range before you write the email.

Which firms provide venture debt?

Set Firm_Types: ["Venture Debt"]. Venture debt sits next to an equity round rather than replacing it, and the lenders are a small, distinct group, so the result set is short and worth reading in full. Add Countries if you need lenders who can actually fund in your jurisdiction.

How many venture capital firms are there in India?

The database does not publish a running national count, and neither should anyone else, because it moves every week. Run the filter and read the number off the result:

{
  "Firm_Types": ["Venture Capital Investor"],
  "Countries": ["India"],
  "Max_Results": 500
}

search_metadata.total_results_found reports how many venture capital firms in India matched. The same pattern works for any country name in English: United Kingdom, Singapore, Canada, Germany.

Is this a startup investors data scraper, or a database query?

The store name says scraper, but nothing is crawled on demand. Every run queries a curated database of 10,469 firms and returns structured JSON in seconds, which is why the inputs are filters rather than URLs, and why the same filters return the same rows tomorrow. Records carry created_at, updated_at, and last_checked so you can see how current each firm is.

Can I call the API programmatically?

Yes. Run it from Python, or from any language that can POST to the Apify REST endpoint:

from apify_client import ApifyClient

client = ApifyClient("YOUR_APIFY_TOKEN")

run = client.actor("johnvc/startup-investors-data-scraper").call(run_input={
    "Firm_Types": ["Venture Capital Investor"],
    "Investment_Stages": ["Series A"],
    "Countries": ["United States"],
    "Include_Contacts": True,
    "Max_Results": 100,
})

for firm in client.dataset(run.default_dataset_id).iterate_items():
    print(firm["firm_name"], firm["firm_website"], firm["firm_stages"])
    for contact in firm.get("investor_contacts", []):
        print("  ", contact["name"], contact["job_title"], contact.get("email"))

Pin apify-client>=3,<4. On version 3 the run object is typed, so it is run.default_dataset_id, not a dictionary key.

Can I use this investor database from an MCP client?

Yes. Connect the Apify MCP server and the actor exposes its full input schema to the model, so you can ask for "pre-seed fintech investors in Germany with contacts" in plain language and get rows back. It works from Claude Code and Claude Cowork (free trial), Cursor, VS Code, Cline, and Windsurf. The agent picks the filters; you still only pay for the firms it returns.

How do I pull an angel investors list or a list of venture capital firms?

Pick the firm type and let it run wide. Firm_Types: ["Angel Investor"] gives you the angel investors list; Firm_Types: ["Venture Capital Investor"] gives you the list of venture capital firms. Both respect Max_Results up to 10,000, and for anything past a single page set "Order_By": "firm_name" and step Offset forward so the pages do not overlap.

Can I filter early stage investors and Series A investors separately?

Yes, and the distinction matters. Series A investors are a single value: Investment_Stages: ["Series A"]. Early stage investors are a bundle, so pass the range you mean: Investment_Stages: ["Pre-Seed", "Seed", "Series A"]. Firms are returned when any stage they invest at matches, and the firm_stages array on each row shows their full range so you can see who is a true early stage fund and who happens to also do seed.

Last Updated: 2026.07.14