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The SuperConnector Club
Non-dilutive funding + warm intros for early-stage founders
8 followers
Non-dilutive funding + warm intros for early-stage founders
8 followers
SuperConnector Club helps early-stage founders grow without giving up equity. The Funding Hub Search 35 verified non-dilutive programs: federal grants, accelerators, and revenue-based financing. Network Miner Import your connections and discover who you know at the companies and funds that matter. Founder Registry $432K+ in verified startup credits from Google Cloud, Anthropic, Stripe, 20+ more. Funding Profile Matching Tell us your preferences then we surface your best-fit programs live.
How does the matching actually work under the hood — is it keyword-based on the program descriptions or do you factor in things like traction, sector, and stage? Curious how much customization there is before the suggestions start feeling generic.
@ayabanc10996 Great question! Our matching is multi-dimensional:
Sector alignment we weight program categories (SaaS, FinTech, HealthTech, etc.) against your founding profile. A climate tech founder gets prioritized for CleanTech grants, not consumer apps.
Stage matching we look at your current stage (pre-seed, seed, Series A, etc.) and surface programs with realistic ticket sizes and milestones. A pre-seed founder won't see Series B+ investor programs.
Traction signals if you've set your monthly revenue or ARR, we factor that in. Revenue-based financing programs bubble up if you have traction; pure equity programs if you're still pre-revenue.
Customization via your Funding Profile you tell us your industry sector, and we use that to weight what shows in your personalized Funding Hub. No generic "all 35 programs at once" it's filtered to your context.
Manual curation our team updates the catalog bi-weekly, adding programs that actually have founders in your stage/sector getting accepted, removing ones with low acceptance rates.
The result: a founder sees ~8-12 highly relevant programs instead of drowning in 35. Way less "spray and pray."
How does the matching actually work once you import your network, is it just keyword overlap or something deeper with the connections graph