Show IH: Built a curated VC database for pre-seed founders — $59 one-time, no $300/mo paywall
Hey IH —
I've been heads-down building a curated VC database for pre-seed rounds. The frustration that started it: most publicly available VC lists are either outdated, untargeted, or behind expensive paywalls that make no sense for a first-time founder.
What I built:
- VCs filtered by sector, stage, and check size — no wasted pitches to funds not investing at your stage
- Verified partner contacts (the actual decision-maker, not the generic inbox)
- Cold email template kit — frameworks based on what actually got responses, ready to customize
Pricing: $59 one-time + optional $9/mo for updates as the list evolves.
Waitlist is live at https://vc.3vo.ai — free to join, launching soon.
Happy to answer questions about how the data is sourced and verified.
— The VC Match Kit team
Trending on Indie Hackers
This is solid — but I think the real constraint here isn’t the data.
At this stage, most founders won’t question what’s inside — they question whether they can trust it enough to act on it.
Especially with cold outreach to VCs, one wrong signal kills confidence.
Curious — have you seen any hesitation coming from perception/credibility, or is conversion mostly straightforward so far?
Really appreciate you raising this — it is probably the most important thing to get right at this stage. You are correct that a wrong signal (e.g. a partner who left the firm, a fund that closed) does more damage than no signal at all. That is exactly why we verify partner contacts directly rather than scraping. Every entry in the database is manually reviewed before it ships, and the optional $9/month tier exists specifically to push removals and replacements as they happen — not just additions. We have definitely seen hesitation from founders who have been burned by stale lists before. The way we address the trust gap is by being transparent about the verification method and offering a refund if any contact bounces or is materially wrong. That removes the one bad entry risk. Happy to show you a sample entry if you want to see the format. What sectors or stages are you focused on?
Makes sense — the verification layer helps reduce risk.
But at this stage, trust isn’t built from process alone — it’s how the product is perceived before usage.
Most founders won’t evaluate methodology deeply.
They decide fast based on whether it feels “safe enough to act on.”
That’s why two similar datasets can perform very differently just based on how they’re positioned.
Right now this reads as a database — but the real value is decision confidence.
If that shift isn’t obvious upfront, hesitation will always exist regardless of quality.