CRM and sales decision
Angel Match
A technical user can build a narrow replacement (searchable DB + CRM + email outreach) in a few weeks, but cannot cheaply reproduce Angel Match’s claimed 125k proprietary, continuously-updated investor dataset or premium data/scale features.
Visit website↗Open-source builds that already do this
Every project below is open source and already does this job today. Fork one, self-host it, or take the parts you need — the build prompt further down assumes an empty file, and this is the shortcut past that. Licences differ; check the one on each card before you ship.
What a replacement has to do
- Provide a searchable investor database, let a user build/export lists, send outreach emails, and track replies in a simple CRM pipeline.
What it still won’t have
- Access to Angel Match’s 125k+ proprietary investor contacts
- Scale and breadth of investor coverage and historical data
- Priority customer support and premium pitch-deck database
- Ongoing data-refresh operations and verification process
- Built-in email outreach limits and deliverability optimizations
What remains hard
- Proprietary data
Angel Match connects you with 125,000+ angel investors and venture capitalists in one platform, helping founders find investors, secure startup funding , and raise capital faster.
- Proprietary data
Our database grew from 700 investors in 2019 to 125,000 angels and VCs today.
First-year cost
Keep paying
Paying is—cheaper in year one.
On cash alone, building overtakes the subscription at 1 seat.
Money you would actually spend
Time you would spend
—
What you would spend
What we assumed
The verdict above measures whether you could build it. This one is only about money.
Runnable build prompt
Build a minimal investor-discovery and outreach web app using: React for frontend, FastAPI (or Express) for backend, Postgres for data, Redis/Celery for background jobs, and SendGrid/Postmark for email. Scope: import investor CSVs, store normalized profiles, implement full-text search and filters (industry, stage, location, investor type), create pipeline UI (create lists, drag/drop cards, status fields), export selected lists to CSV, send personalized bulk emails with per-recipient merge fields and record send/open events, basic inbox to record replies, authentication, and role-based access for one user. Out of scope: acquiring a 125k proprietary contact dataset, pitch-deck marketplace, advanced deliverability features, paid integrations. Include input validation, error handling, background job retries, and unit tests for import, search, export, and email-sending flows.
How we checked
How the score was reached
- Partly verdict base52
- An open-source build was found+5
- 4 cited sources+3
- Price verified on pricing page+3
- 3/3 assessment runs agreed+4
- Hard moats found in the evidence-3
- Evidence score64
The base comes from the verdict. Everything under it is a check that either happened or did not, and each one is a fact frozen in this record rather than a judgement made at render time — so the same evidence always produces the same number.
How scoring works →Cited sources · 4
Every page the run actually retrieved.
- official productAngel Match — product
- official pricingAngel Match — pricing
- open sourcefrappe/crm
- open sourceDjango-CRM/Django-CRM
Integrity checks
What held up, and what did not.
