We recently published an article on how we’re building our own internal AI infrastructure for VC here at Draper. Custom workflows to help our team gather information faster, so they can get back to the true human work in VC: meeting with and being present with founders.
In 1985, I built my deal flow by knocking on the doors of the ten or so venture capitalists that existed and asking them to send me the deals they were declining. I needed to build knowledge so I could build judgment.
Forty years later, the team at Draper Associates built something I could only have dreamed of back then:
-One centralized database that holds a singular record per company that has all our internal data as well as enriched data from outside verified sources like Harmonic
-A machine learning model, trained on 40+ years of successes and passes, that reads the hundreds of deals we get every week and surfaces the best fits directly to the investment team
-A brief on every meeting before we walk in
-Warm intros drafted from a network of 15,000+ contacts
-Answers to any question from our own records in plain English across 400+ portfolio companies (and an extra info assist from our Harmonic API)
The AI/ML infrastructure handles the routine work, but judgment remains human: sitting across from a founder, recognizing a missionary, making the call while the idea still sounds crazy.
Now there are more hours for exactly that.
Read more about how we built this system, philosophically and practically: https://www.draper.vc/newsroom/how-we-built-drapers-ai-stack
In 1985, I built my deal flow by knocking on the doors of the ten or so venture capitalists that existed and asking them to send me the deals they were declining. I needed to build knowledge so I could build judgment.
Forty years later, the team at Draper Associates built something I could only have dreamed of back then:
-One centralized database that holds a singular record per company that has all our internal data as well as enriched data from outside verified sources like Harmonic
-A machine learning model, trained on 40+ years of successes and passes, that reads the hundreds of deals we get every week and surfaces the best fits directly to the investment team
-A brief on every meeting before we walk in
-Warm intros drafted from a network of 15,000+ contacts
-Answers to any question from our own records in plain English across 400+ portfolio companies (and an extra info assist from our Harmonic API)
The AI/ML infrastructure handles the routine work, but judgment remains human: sitting across from a founder, recognizing a missionary, making the call while the idea still sounds crazy.
Now there are more hours for exactly that.
Read more about how we built this system, philosophically and practically: https://www.draper.vc/newsroom/how-we-built-drapers-ai-stack