In Part II, we reveal more details about startup funding in the Triangles startup ecosystem including, by stage, amounts raised with high/lows, valuations, discounts and more!
Fantastic breakdown of the funding landscape! The 46% SAFE dominance across all rounds is telling, but what really caught my eye was how the valuation factors shift from 80% founder-centric at pre-seed to 50% progress-driven at Series A. I've seen firsthand how founders struggle with the transition from selling their vision to proving unit economics, and this data frame makes it way clearer where that inflection actualy happens. The juggling analogy nails it too.
The point about public-market comps for private valuations really got me thinking. How do dynamic tools like Benchsights refine this approach for early-stage startups compared to static tables?
Hey @rainbow roxy! Unfortunately there's no source for this information that's comprehensive. The best is a company called pitchbook, but it's $$$ and not all companies disclose. Cart has good data, but one trick is I find here in the Triangle we are scrappy (aka cheap) and carta adoption is low, so their data set really misses our ecosystem because it's based on a paid-system. Even our data is from companies we've invested in which, because of our model, is pretty much 90%+ at seed/pre-seed, but still not 100%.
I think the best bet is to look at the data crunchbase, pitchbook and carta put out, marry that with what we provided here and you kind of can triangulate to what you want.
Great read for a Monday morning! Thank you for sharing. This article allowed me to reflect on where we are today, and made me feel good about where we are in our journey, and what our initiatives are for the coming months and in 2026!
Fantastic breakdown of the funding landscape! The 46% SAFE dominance across all rounds is telling, but what really caught my eye was how the valuation factors shift from 80% founder-centric at pre-seed to 50% progress-driven at Series A. I've seen firsthand how founders struggle with the transition from selling their vision to proving unit economics, and this data frame makes it way clearer where that inflection actualy happens. The juggling analogy nails it too.
Thanks - appreciate the feedback!
The point about public-market comps for private valuations really got me thinking. How do dynamic tools like Benchsights refine this approach for early-stage startups compared to static tables?
Hey @rainbow roxy! Unfortunately there's no source for this information that's comprehensive. The best is a company called pitchbook, but it's $$$ and not all companies disclose. Cart has good data, but one trick is I find here in the Triangle we are scrappy (aka cheap) and carta adoption is low, so their data set really misses our ecosystem because it's based on a paid-system. Even our data is from companies we've invested in which, because of our model, is pretty much 90%+ at seed/pre-seed, but still not 100%.
I think the best bet is to look at the data crunchbase, pitchbook and carta put out, marry that with what we provided here and you kind of can triangulate to what you want.
Great read for a Monday morning! Thank you for sharing. This article allowed me to reflect on where we are today, and made me feel good about where we are in our journey, and what our initiatives are for the coming months and in 2026!
Thanks Hill!