Recent advances in Natural Language Processing have ushered in a new era of Natural Language Understanding. Coupled with advances in Graph databases and traditional Network Theory, the venture process is finally ready for a revolutionary upgrade.
VCs know their greatest asset is their network… yet few apply cutting edge technology to their network process. Most VCs are plagued by Dunbar’s number; relying on memory & adversely affected by recency bias, thus underutilizing their network.
Tools like Affinity have emerged as a way to provide VCs with an “easy win” to organize their networks but, there are many shortcomings with these tools. The biggest is their generalist approach to network indexing… just look at Affinity’s website…
They are proud to provide tags like “Startup” and “Mobile”. How are those tags supposed to help you find the perfect match for your very specific diligence questions or recruiting needs from the thousands of nodes in your network?
A CRM like Affinity can’t scale their NLP indexing beyond basic tags because it is not economically viable for their business… and the other industries they focus on like Real Estate & Enterprise Sales don’t benefit from additional indexing.
VCs love to ask Why Now? NLP has become advanced & commoditized enough that it is viable to use in-house to build custom datasets on individual & firm-sized networks.
Using custom NLP we can create extremely deep network indexing to tag network nodes on a much more specific level. We can utilize a node’s full corpus of content; articles published, about pages, jobs / organizations history, social etc... to generate deep understanding of a node’s domain expertises and networks they have access to.
Just think about what this unleashes for the venture process...
Automated recommendations for
- Customer introductions
- Portfolio advisors
- Recruiting matches
- Network introductions
- Email labeling / sorting
Deep language understanding can go beyond a VCs existing network & email. The same deep language understanding & network theory can be used to map out top network nodes in new investment verticals as they arise.
Deep language understanding & network mapping, coupled with advances in natural language generation can jumpstart any diligence process. Automate market overviews, research summaries, algorithmically ranked network nodes (in & out of existing network), benchmark data, competitors etc... all in frontier industries that haven’t been captured by the slow moving service providers like CB insights.
It’s time for VCs to invest in applying technology to upgrade their process. Many of the top firms have already started. We’d love to help.
Feel free to Request a Demo. There are many more areas that we didn’t cover in this article, specifically around operational improvements, where we can help as well.