1Mby1M Virtual Accelerator Investor Forum: With Scott Sandell of NEA (Part 2)

Sramana Mitra: For those of you who don’t know the history of WebEx, the company went public and was eventually acquired by Cisco. It was a very successful story. It was one of the first two cloud companies in the history of the business. I want to get to Salesforce, but let me actually first get to Tableau because it’s a more contemporary company.

I’ve written about Tableau quite a lot recently. My understanding of Tableau was by the time they came to NEA for their funding, the company not only had customers and revenues, but it also had done an interesting OEM deal with Hyperion. Tell us a bit about what you saw in Tableau. It seems like an incredibly capital efficient company that generated immense return on investment. >>>

1Mby1M Virtual Accelerator Investor Forum: With Venktesh Shukla of TiE Angels (Part 5)

Sramana Mitra: There is actually a pre-seed problem. There were 70,000 companies that received some sort of early-stage financing. In the last few years, these numbers have been very high but the number of companies that get venture financing remains at 1,200 or so.

In the middle where there are companies that have crossed over to being credible companies, that set of companies is actually much lower. A lot of companies are getting funding from, for a lack of better word, dumb investors who don’t know what they’re doing and just writing checks and creating a glut in the funnel. But it’s in the middle where you have good companies. >>>

1Mby1M Virtual Accelerator Investor Forum: With Scott Sandell of NEA (Part 1)

Responding to a popular request, we are now sharing transcripts of our investor podcast interviews in this new series. The following interview with Scott Sandell was recorded in February 2015.

Scott Sandell, General Partner at NEA, is one of NEA’s star investors. He has been named to the Forbes Midas list every year since 2007, and has been involved with eight Unicorn companies including Salesforce.com, Workday, Webex, Tableau, and others. Scott discusses, specifically, Webex and Tableau in quite a bit of depth. In both companies, the scrappy, capital-efficient management of those businesses were striking!

Among Silicon Valley’s venture firms, NEA holds a special place in my own entrepreneurial journey, being the first VC firm that I >>>

1Mby1M Virtual Accelerator Investor Forum: With Venktesh Shukla of TiE Angels (Part 4)

Sramana Mitra: Of your ventures that have raised venture money, have they raised venture money from these $75 million to $100 million funds, or have they raised money from the bigger funds?

Venktesh Shukla: They typically raise money from bigger funds because these are big spaces. One of them was how do you handle structured and unstructured data. Every company in the world has that problem and there is no solution. With the onset of predominantly mobile access, the old networking problems haven’t gone away. The new ones have piled on top of that.

Using machine learning, how do you isolate the problem when somebody complains that he’s seeing poor responsiveness? That’s a new category of problem. The third one is how do you create a virtual private cloud in minutes. The traditional route of >>>

1Mby1M Virtual Accelerator Investor Forum: With Venktesh Shukla of TiE Angels (Part 3)

Sramana Mitra: You can play this with a very specific domain focus with a specific set of corporate around you. In some cases, these corporates are investing in these little micro-funds that play this game. It is a little side of the industry that is developing. There are these little niches which are not venture-scale niches. They’re not going to be venture-fundable. You can only play these if you work with little bits of seed money and then, pretty much, go straight to acquisition and not go out to raise a venture round.

Venktesh Shukla: Absolutely. It is to critical to understand not only the niche and the technical chops but also the relationship in that target ecosystem. Do you have a member in your team that has that visibility and relationship with the key players in the industry? >>>

1Mby1M Virtual Accelerator Investor Forum: With Venktesh Shukla of TiE Angels (Part 2)

Sramana Mitra: I’ll provide a bit of commentary for the audience on some of the things that you mentioned as trends. We’ve also seen this unstructured data problem being solved. For a couple of decades, there have been major companies that have been formulated on this unstructured data problem. Autonomy was one of them that went very big.

Today, one of the trends that we’re seeing is this whole unstructured data problem being solved for specific verticals or specific functional areas and solutions built on top of that unstructured data problem in a cloud-

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1Mby1M Virtual Accelerator Investor Forum: With Venktesh Shukla of TiE Angels (Part 1)

Responding to a popular request, we are now sharing transcripts of our investor podcast interviews in this new series. The following interview with Venktesh Shukla was recorded in September 2017.

Venktesh Shukla, founder of TiE Angels and General Partner Monta Vista Capital, discusses some shifts happening in the world of seed investing.

Sramana Mitra: Tell us about TiE Angels and how you work with investors and entrepreneurs.

Venktesh Shukla: TiE Angels is a 7-year-old organization that is a collection of individual investors who, in general, tend to focus on B2B companies. The whole idea is that the collective wisdom of the group helps make better decisions, >>>

1Mby1M Virtual Accelerator Investor Forum: With Shomit Ghose of Onset Ventures (Part 3)

Sramana Mitra: Elon Musk has talked a lot more along the lines of what you’re talking about – the unintended consequences of AI or even AI running amok in an evil way. I dealt with more of the economic question. Machine learning is really at the absolute beginning. We’re probably talking about a 50-year cycle but machine learning being machine learning has an incredibly-fast capacity to become very powerful.

In the next 50 years, I’m positive that we’re going to see machine learning penetrating every aspect of the human endeavor. If that really starts to take over professions or shrink professions in huge numbers, then 

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