VC

Show us the way, Teaching Staff

Tuesday after our VC presentation and we show up at the loft ready for our SGM with Jay and the teaching staff. Feelings are mixed as we know we have a product idea that according to the VCs can "bring a lot of value" (so we are excited) yet is "highly dependent on our modeling layer" (so we are scared and unsure). We are going in to the SGM looking for some guidance. 

Thankfully, our CS210 staff gave us just that. One of the TAs led us through some procedural/infrastructure considerations, leading to creation of this blog and usage of our GitHub to track and assign issues. This was very helpful, but the more meaningful insight came from Jay who had further feedback from the VCs and plenty of personal opinions regarding our "Big Data to Small Data" exploration platform. 

Basically, it sucked. The use cases were unclear, the data was unavailable, the models didn't exist, the team was unclear if we could pull it off... the list goes on. Basically Jay told us that all our creeping suspicions and fears were justified and that we needed to better define our users and the actionable ways in which they could benefit from our product. He also thought our product was maybe too ambitious and that we needed to remember "it is better to under-promise and over-deliver than over-promise and under-deliver." With this input, we realized we had a lot of work to do, and planned an emergency pivot meeting that night in the only place we felt appropriate- the d.school. 

under-promise and over-deliver
— Jay Borenstein

VC Day

Thanks to Jay's connections in the industry, the entire class was able to pitch their project proposals to a panel of Venture Capitalists: John Lilly of Greylock, David Hornik of August Capital, and George Zachary of Charles River Ventures. This was an amazing opportunity to get industry opinions about our proposed projects from individuals who know what works and what doesn't. 

It was very entertaining to see our peers present their respective products, but eventually we had to face the music and present our product. Equipped with our slide deck we pitched our "Big Data to Small Data" product with the title "Explore Big Data." Our presentation went smoothly and it was time to hear the million dollar input from the VCs. 

After joking about how we wanted to take on Splunk and Domo (as two of the VCs were affiliated with these companies) we learned two main things: 

  1. A product like this is extremely valuable, predicated on the proper function of our models. 
  2. Creating models that scale and continue to give insight is very hard.

We found this input to be very valuable and would like to thank these assumably very busy men for their time. Unfortunately we began sensing a theme: did we bite off more than we could chew with this ambitious product?