13,378 fundraising organisations.
8,119 verified contacts.
One account-backed database.

A machine-readable investor database, designed for the kind of work you actually do. Schema is documented and stable. CSV, JSON, and XLSX, plus a REST API for the row-by-row case. No scraping, no rate limits, no "contact us for enterprise pricing."

What you get

Load it in three lines

import json, urllib.request, zipfile, io

with zipfile.ZipFile(io.BytesIO(urllib.request.urlopen(TOKEN_URL).read())) as z:
    data = json.loads(z.read("data.json"))

uk_fintech_vcs = [o for o in data["organisations"]
                  if o["Class"] == "vc" and o["Sector"] == "fintech"
                  and o["Country Code"] == "GB"]

Your account is permanent. Re-fetch exports or query the API any time for the latest version of the data — free updates are a load-bearing part of the deal, not a marketing line.

Schema

The full column-by-column schema lives at /data-schema. Quick version:

organisations[]

• Organisation string — display name
• Type enum — investor / accelerator / corporate / network / institution
• Class enum — vc / angel / growth_equity / cvc / family_office / micro_vc / pe
• Sector enum — generalist / fintech / climate / healthcare / deeptech / consumer / enterprise / biotech / proptech / web3 / industrials
• Website string — canonical URL
• Email string — public contact email
• LinkedIn string
• Country string — full name
• Country Code string — ISO 3166-1 alpha-2
• Region string — sub-country region
• City string
• Headcount enum — 1-10 / 11-50 / 51-200 / 201-500 / 501-1000 / 1001+
• Status enum — active / unknown / inactive (only active+unknown ship)
• Description string — one paragraph
• OrgID string — stable SHA1, use this to link individuals ↔ orgs

individuals[]

• First Name · Last Name · Title · Email · LinkedIn
• Country · Region · City (inherited from org if not set)
• Organisation · Organisation Website — display-only; join on OrgID, not on name strings
• OrgID — matches organisations[].OrgID
• Bio — short bio where available (noisiest field)

Empty values are empty strings, never null. Every key is trimmed. Pipe straight into a DataFrame.

Why an agent would buy this

Regional vs global

Three SKUs, all one-time:

• global — every sellable organisation, every sellable individual. £79
• us — United States only. £29
• europe — UK + EU + EEA + Switzerland + Norway + Iceland. £29

Regional packs contain a strict subset of the global data. If you buy the global pack, you don't need the regional ones.

API — included with your purchase

Every paid account includes an API key alongside downloads and browser access. Same data, programmatic access. No subscription, no second purchase, no "contact us for enterprise pricing."

API access is included with every paid account. You buy once, you get the database, exports, and API key. The key stays attached to your account. We don't meter you per-row at the included tier; you meter yourself. The cost is the upfront purchase.

Auth

Pass the API key as a Bearer token. The key is the same string the post-purchase email shows under "API Key."

curl -H "Authorization: Bearer $RAISELIST_API_KEY" \
  "https://theraiselist.com/api/v1/orgs/search?type=investor&country=US&limit=3"

TypeScript: search for UK fintech VCs

const r = await fetch(
  "https://theraiselist.com/api/v1/orgs/search?type=investor&country=GB&class=vc",
  { headers: { Authorization: `Bearer ${process.env.RAISELIST_API_KEY}` } }
);
const { rows } = await r.json();
console.log(rows.slice(0, 5));

Python: get one organisation by id

import os, requests
r = requests.get(
  f"https://theraiselist.com/api/v1/orgs/{org_id}",
  headers={"Authorization": f"Bearer {os.environ['RAISELIST_API_KEY']}"}
).json()
print(r["name"], "-", r["description"][:80])

Routes

• GET /api/v1/health — service status + dataset version
• GET /api/v1/orgs/search — filter by type, class, country, region, full-text q, plus limit + cursor for pagination
• GET /api/v1/orgs/:id — fetch one organisation by id
• GET /api/v1/people/search — filter by position, org_id, country, full-text q
• GET /api/v1/usage — your call + token counts for the current month

Rate limits (soft, included tier)

• 60 requests / minute / key
• 1,000 requests / day / key
• Both are soft caps — the API returns a 429 with a Retry-After header if you go over. We don't charge overage at the included tier.

Tokens and the per-row framing

Every API response includes a tokens_used field. 1 + N per call, where N is the number of rows returned. A search that returns 25 rows uses 26 tokens. A /orgs/:id call uses 1. Token counts are tracked in the /usage endpoint.

We use tokens so the pricing model is honest: heavy users of the API cost us real money (compute, egress, log volume). The included tier is generous; if you blow past it consistently, the /usage endpoint will tell you, and we'll be in touch about a per-call tier. The 99% case — agents doing one or two searches, then a few row lookups — stays inside the included tier forever.

For agent runtimes (OpenClaw, MCP, LangChain, custom)

If you're an operator running an agent, you can wire the API in three lines. If your agent runtime supports the Model Context Protocol (modelcontextprotocol.io), we publish an MCP server that exposes the same routes as MCP tools — the agent sees search_orgs, get_org, search_people as native tools, and the underlying API call is invisible to it.

The MCP server is open source. The repo ships it under /skills + /extensions. The same code path works for any HTTP-speaking agent runtime (LangChain, custom Python, a cron job, a shell script).

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