VC Investor Watchlist 💼

foXLabs company-intelligence series: Company enrichment · Owler · Craft · Built In · Free lookup · Location intelligence

🎉 Turn public VC data into a clean, structured investor watchlist — no login, no API key, one row per investor, with focus, stage, portfolio signals and links. Built for founders, fundraising and BD teams tracking investors.

🔍 What is the VC Investor Watchlist — and when should you use it?

Give this actor investor or firm names and it returns matching investors from public venture-capital and investor sources — as clean, deduplicated rows you can filter, export or feed to an AI agent. Every run reads the source live.

Use it when you need: an investor list for outreach; a portfolio snapshot before a call; or a starting point for fund research.

Use something else when: you need LP or fund-financial detail — this tracks investor profiles and signals, not fund financials.

🤖 Use with AI agents

Already on the Apify MCP server? Ask for this Actor by name: foxlabs/vc-investor-watchlist.

Your agent can pay for its own runs. This Actor is pay-per-event with agentic payments, so an agent can discover it, run it and settle the bill over x402 (USDC on Base) or Skyfire — no Apify account or API token of its own. Billing is the same either way: per delivered record, never for errors.

Otherwise paste this into Claude, ChatGPT, Cursor or any MCP-enabled assistant:

I want to pull investor company records using the Apify Actor `foxlabs/vc-investor-watchlist`.
Input: `companyNames` is a list of investor or firm names; `companyDomains` takes domains such as `sequoiacap.com`; `companyUrls` takes exact Owler URLs. The `include*` switches control which sections are fetched, and `maxResults` caps how many investors are looked up.
Start with: {"companyNames":["Sequoia Capital","Andreessen Horowitz","TPG"],"maxResults":50}
Ask me what to look up, run the Actor, then summarise the rows as a table.

The machine-readable API, MCP config and OpenAPI definition live at apify.com/foxlabs/vc-investor-watchlist.md.

📋 Overview

Everything you need to turn public venture-capital and investor sources into clean, structured data — in one actor, with no login, cookies or API key.

Why teams pick this actor:

• ✅ Whole dataset, one call — name or ID in, matching investors out.
• 🧹 No empty-promise columns — only fields this registry actually fills; degenerate columns are removed.
• 🔗 Stable identifiers — every row carries the source's own IDs, ready to join across runs and to other Fox Labs actors.
• 💰 Per-row pricing — a minimal price per delivered row, no subscription.
• 🤖 Agent-ready — MCP + x402 agentic payments.

✨ Features

• 🔍 Name or ID lookup — relevance-ranked name search or exact registry-ID lookup.
• 🏢 Full entity profile — status, legal form, formation date, address and the registry’s own contact fields.
• 🧹 Clean schema — deduplicated camelCase rows, ready for CSV/Excel/JSON.

🎬 Quick Start

curl -X POST "https://api.apify.com/v2/acts/foxlabs~vc-investor-watchlist/runs?token=YOUR_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"companyNames":["Sequoia Capital","Andreessen Horowitz","TPG"],"maxResults":50}'

🚀 Getting Started (3 steps)

1. Choose your targets — investor or firm names.
2. Set the cap — maxResults limits how many investors are looked up (default 50).
3. Run and export — get a clean dataset as JSON, CSV or Excel.

📥 Input

{"companyNames":["Sequoia Capital","Andreessen Horowitz","TPG"],"maxResults":50}

Field	Type	Description
companyNames	array	Investor or firm names, one per line.
companyDomains	array	Domains such as sequoiacap.com.
companyUrls	array	Exact Owler company URLs, or a .txt / .csv upload.
includeInvestments / includeAcquisitions / includeFunding	boolean	Portfolio investments, acquisitions and funding rounds (all default on).
includeCompetitors / includeNewsEvents / includeFinancialHistory	boolean	Competitor set, key highlights and revenue history (all default on).
includeLeadership / includeSocial	boolean	Leadership team and social profiles (both default on).
maxResults	integer	Most investors looked up in one run (default 50).
maxConcurrency	integer	Profile pages fetched in parallel (default 10).
proxyConfiguration	object	Apify proxy settings.

📤 Output

One row per company, saved to the dataset. Every row carries scrapedAt. Lookups that cannot be completed are reported in the run log and in the FAILED_LOOKUPS record in the key-value store — they are not written to the dataset, so they are not charged.

Field	Description
url	Url
inputQuery	Input Query
resolvedVia	Resolved Via
name	Name
legalName	Legal Name
description	Description
summary	Summary
website	Website
domain	Domain
logo	Logo
industry	Industry sector as shown on the source — not a NACE or SIC code
industries	Industries
industrySectors	Industry Sectors
ownership	Ownership
yearFounded	Year Founded
headquarters	Headquarters
address	Principal address
phoneNumber	Phone Number
exchange	Exchange
ticker	Ticker
ceo	Ceo
leadership	Leadership
employees	Registered employee count
employeesFormatted	Employees Formatted
employeesRange	Employees Range
revenueAmount	Revenue Amount
revenueFormatted	Revenue Formatted
revenueRange	Revenue Range
followers	Followers
totalAcquisitions	Total Acquisitions
totalInvestments	Total Investments
acquisitions	Acquisitions
acquisitionsTruncated	Acquisitions Truncated
investments	Investments
investmentsTruncated	Investments Truncated
firstInvestment	First Investment
keyHighlights	Key Highlights
revenueQuarterly	Revenue Quarterly
momentum	Momentum
fundingByYear	Funding By Year
sicCodes	Sic Codes
funding	Funding
competitors	Competitors
totalCompetitors	Total Competitors
social	Social

💼 Use cases

1. Fundraising targeting — build a targeted investor list by focus and stage. Input: investor names. Output: investors + focus + stage. Use: a warm outreach list.

2. Competitor funding — watch which investors back a space. Input: firm names. Output: investor + portfolio signals. Use: map the cap table landscape.

3. BD / partnerships — find investors active in a sector. Input: names. Output: investor profiles. Use: shortlist partners.

🔗 Integration

JavaScript / Node.js

import { ApifyClient } from 'apify-client';
const client = new ApifyClient({ token: 'YOUR_TOKEN' });
const run = await client.actor('foxlabs/vc-investor-watchlist').call({"companyNames":["Sequoia Capital","Andreessen Horowitz","TPG"],"maxResults":50});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items[0]);

Python

from apify_client import ApifyClient
client = ApifyClient('YOUR_TOKEN')
run = client.actor('foxlabs/vc-investor-watchlist').call(run_input={"companyNames":["Sequoia Capital","Andreessen Horowitz","TPG"],"maxResults":50})
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

Written for apify-client 3 for Python, where call() returns a run object; with version 1 or 2 it returns a dict — write run['defaultDatasetId'] there.

Automation (n8n / Zapier / Make): schedule or webhook → HTTP request to the actor API with your input list → handle the JSON dataset → push to a sheet, CRM or dashboard.

📊 Pricing

Pay-per-event: per row written to the dataset. Lookups that fail are not written to the dataset — they go to the run log and the FAILED_LOOKUPS record in the key-value store — so they are never charged.

❓ FAQ

Do I need an account, login or API key? No. This reads public venture-capital and investor sources.

What do I search by? Investor or firm names.

How current is the data? Every run reads public company profiles on Owler live, so results are as current as the source.

What investor data is included? Investor/firm profiles — focus areas, stage, portfolio signals and links as published on public sources.

Can I export to CSV / Excel / JSON? Yes — directly from the Apify dataset.

🐛 Troubleshooting

• Fewer rows than expected — raise maxResults, or refine the input.
• A name returns an unexpected entity — it matched a similar registered name; search the exact registry ID.
• No rows for a name — try the entity’s exact legal name or its registry ID.

⚖️ Is it legal to scrape this data?

This actor reads publicly available investor and venture-capital information. Results can still contain personal data (e.g. a person’s name); personal data is protected by the GDPR and similar laws, so only process it with a legitimate basis. See Apify’s blog post on the legality of web scraping.

🤝 Support & contact

• 🌐 Website: data.foxlabs.com.tr
• 📧 Email: info@foxlabs.com.tr
• 🐛 Issues: open a ticket in the Actor’s Issues tab
• 🧰 More clean B2B data actors: Fox Labs on Apify

Changelog

0.5.18 — 2026-10-08 — README: the Python example works with the current Apify client

• The README's Python example read the results with run['defaultDatasetId']. With the current Apify client for Python (version 3) call() returns a run object, not a dict, and that line raised TypeError: 'Run' object is not subscriptable — after the run itself had finished. The example now reads run.default_dataset_id; with client version 1 or 2, keep run['defaultDatasetId']. Checked with apify-client 3.2.1, 2.5.1 and 1.12.2.
• No code, output field or pricing change.

0.5.17 — 2026-09-20 — README corrected against the real input schema

• Every code example was broken. The AI-agent, cURL, JavaScript and Python examples used keys that do not exist in this Actor's input schema (queries, maxResultsPerQuery) with a literal placeholder string instead of a real value, and the input table listed those phantom fields instead of the real ones. Anyone who copied an example got a failing run. All examples now match the schema prefill exactly.
• Removed promises the Actor does not keep: "formation / status monitoring", "a canonical registry record for KYB and due diligence", and "every row carries query" (there is no query field). Fixed a duplicated word in the intro.
• Billing wording corrected. The README said "empty/failed lookups are never billed" without saying why. Failed lookups are not written to the dataset at all — they are reported in the run log and in the FAILED_LOOKUPS record in the key-value store — so there is no row to charge. Stated plainly instead of implied.
• No code, output field or pricing change.

0.5 — 2026-09-07

• Enabled AI-agent payments (x402) + rebuilt the README to the full standard (What-is / when, AI-agents + x402 agentic payments + MCP, Overview, Features, Use cases, Integration, FAQ, Troubleshooting, Support & contact).

0.0

• Initial release: data from public venture-capital and investor sources by name or registry ID.