I. A data-driven what??
The ones of you who know me are very well aware that if there is something which has sort of obsessed me for the last few years, this is definitely how to use analytics and AI to improve the venture industry.
While I tended to focus on scouting and evaluation, I learned that AI can be also used to spot general trends, identify market gaps, improve VCs portfolio management, better match co-investors, and deals, gather intelligence on competitors’ landscape, identifying potential acquirers, and improve pricing models.
I have been thinking about those issues for a while now (and stay tuned because I will post over the next few months my latest research in this field), and did already write on the importance of using AI in VC, summarized some academic research on this topic, and generally wrote about AI investors and accelerators.
I am clearly not the first one who is arguing for a data-driven approach to investing, and I thought it would have made sense to write a short post on other same-minded investors that I got to know or heard of.
Knowing exactly what they do is quite cumbersome without having inside information, so I am simply reporting public knowledge as well as what I read and heard on venture funds using AI to some extent (in alphabetic order):
- 645 Ventures: Series A investor, they follow a data-intensive approach that mostly helps them in deal sourcing and evaluation (and they have a fairly specific metrics-driven process to invest Growth Seed in a bunch of different sectors). They also seem to automate many of the traditional VCs manual tasks;
- Ardian: a world-leading private investment house, they are enhancing their AI capabilities through partnerships with startups that can collect and analyze unstructured market data;
- Clear Ventures: they use AI to let their portfolio companies to intelligently connect to…