Apify pre seed investors

Pre Seed Investors: Stage-Filtered Outreach Lists

Build an investor outreach list for a raise. Filter a curated database of 10,469 firms to the investors who actually invest at your stage and in your space, and get partner contacts with job titles, emails when available, and check sizes, ready for a CRM.

When to use this skill

• The user is raising and wants to find pre seed investors, seed investors, or early stage investors.
• They want an investor lead list scoped to an industry, stage, firm type, or country.
• They want partner-level contacts (names, titles, LinkedIn, check sizes) for outreach.
• They ask "who invests at pre-seed in fintech" or "make me a target list for my raise".

Not for: personalized investment advice or intro-making (this collects research and outreach data), city-level filtering (country only), or startup-side funding data.

What you get

One row per matching firm: firm_name, firm_description, firm_city, firm_country, firm_website, firm_linkedin_url, firm_stages, firm_aum, firm_focus, industry_names (plus crunchbase_url and social links when on file). With Include_Contacts true (the point of this workflow), each firm adds investor_contacts, empty when no contacts are on file: name, job_title, email when available, linkedin_url, and minimum, maximum, and target check sizes, the fields an outreach row needs.

Prerequisites

• Apify account (sign up at https://apify.com?fpr=9n7kx3&fp_sid=skillrepo).
• Authentication via apify login, or an APIFY_TOKEN environment variable (Apify Console, Settings, Integrations).

The Actor

• Store page: https://apify.com/johnvc/startup-investors-data-scraper?fpr=9n7kx3&fp_sid=skillrepo
• Actor ID: johnvc/startup-investors-data-scraper
• Pricing: pay per firm returned plus per contact (see references/gotchas.md).

Run it with the Apify CLI

Pre-seed investors in AI, with contacts:

apify actors call "johnvc/startup-investors-data-scraper" -i '{"Investment_Stages":["Pre-Seed"],"Focus_Areas":["Artificial Intelligence"],"Include_Contacts":true,"Max_Results":25}' \
  --json \
  --user-agent apify-awesome-skills/apify-pre-seed-investors \
  2>/dev/null

Early-stage bundle (pre-seed through Series A) among angels and VCs in the United States:

apify actors call "johnvc/startup-investors-data-scraper" -i '{"Investment_Stages":["Pre-Seed","Seed","Series A"],"Firm_Types":["Venture Capital Investor","Angel Investor"],"Countries":["United States"],"Include_Contacts":true,"Max_Results":30}' \
  --json \
  --user-agent apify-awesome-skills/apify-pre-seed-investors \
  2>/dev/null

Every call carries the three flags this repo expects: --json, --user-agent apify-awesome-skills/apify-pre-seed-investors, and 2>/dev/null.

Run it from Claude or another AI agent (MCP)

The Actor is MCP-ready. Add the hosted server URL:

https://mcp.apify.com/?tools=actors,docs,johnvc/startup-investors-data-scraper

Then ask, for example: "Find 25 pre-seed investors in climate tech with partner contacts and check sizes, and format them as an outreach sheet." MCP setup docs: https://docs.apify.com/platform/integrations/mcp

Workflow

1. Scope the raise. Map the user's stage to Investment_Stages (a raise usually spans two: ["Pre-Seed","Seed"]), their space to Focus_Areas, and any geography to Countries (full English names).
2. Pick firm types. Pre-seed lists usually want Firm_Types ["Venture Capital Investor","Angel Investor"] (exact enum strings); add accelerators or family offices when the user asks.
3. Turn contacts on. Include_Contacts true is what makes this an outreach list rather than a market map.
4. Bound and estimate. Max_Results 20 to 30 keeps the first pass around $2 to $3; confirm before bigger pulls. See references/gotchas.md.
5. Run, then shape for outreach. Flatten investor_contacts to one row per contact (firm, name, title, email, LinkedIn, target check size). Flag rows without email for LinkedIn-first outreach.
6. Qualify against check size. Filter out contacts whose minimum check exceeds the round, using the min, max, and target check fields.

Inputs

• Investment_Stages (text list, Pre-Seed to IPO): the stage filter this workflow centers on
• Focus_Areas (enum, about 48 industries) and Firm_Types (enum, 17)
• Countries (full English names), Keyword (free text)
• Include_Contacts (true for outreach), Max_Results (cost cap), Offset

Cost

Per firm plus per contact: a 25-firm pull with contacts lands around $2 to $3. Larger sweeps scale linearly; estimate and confirm first. Live prices and thresholds are in references/gotchas.md.

Honest limits

• Emails are present only when available; some contacts are LinkedIn-only.
• Country filter only; "investors in Boston" needs a US pull filtered client-side on firm_city.
• The data supports outreach research; whether an investor is a fit is the founder's call, and this skill gives data, not investment advice.

Troubleshooting

• Too few firms: widen Investment_Stages by one stage or drop Focus_Areas; stage tagging varies by firm.
• No contacts on some firms: expected; not every firm carries contact rows. The firm's LinkedIn URL still supports manual lookup.
• List feels generic: add Keyword (for example "developer tools") to narrow within an industry.

See references/gotchas.md for cost guardrails and error recovery, and references/actor-index.md for the Actor routing table.

Related company-data Actors

• Crunchbase Company API: https://apify.com/johnvc/crunchbase-company-api?fpr=9n7kx3&fp_sid=skillrepo
• PitchBook Company API: https://apify.com/johnvc/pitchbook-company-api?fpr=9n7kx3&fp_sid=skillrepo
• LinkedIn Company API: https://apify.com/johnvc/linkedin-company-api?fpr=9n7kx3&fp_sid=skillrepo