Europe/Israel Enterprise/Tech Weekly

The Angle Issue #36: August 27, 2018

For me, as a VC working to perfect my game, Benchmark has always been the VC firm that set the standard. This week saw two interesting pieces covering this incredible firm:

• The first is this fantastic profile in the WSJ which captures what makes the firm so unique: "The leaner model has worked. Its 2011 fund, the firm’s seventh, boasts investments in nine companies valued at $1 billion or more, according to a person familiar with the figures. Overall the fund has racked up more than $14 billion in cash and paper gains for the firm and its investors, the person said. The figures value the private companies in the portfolio at the price of their most recent round of funding, the person said."

• The second is an interview with Benchmark's Sarah Tavel. The conversation touches on her own career, the prevalence of mega-rounds, and more. Most interesting to me was this simple, honest, observation on where there isn't a Benchmark London or Benchmark Israel anymore: "We went through a period very soon after our founding when we did try to scale. We had Benchmark London, Benchmark Israel, we had more GPs in our Silicon Valley office — and our returns suffered. For us, that was a lesson that in order to be the best, we had to focus and stay lean." 

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Please feel free to email me with comments (or startups) and if you like this - please forward to friends. Thanks!

From the blog

1Q18 & 2Q18 EU+IL VC Data.
$12.7B of VC investment summarized in 70 slides. 

Europe/Israel Enterprise/Tech

• Scotland/Fintech. A look at the ID Company, which addresses the fintech onboarding challenge.

• Israel/Conversational Intelligence. A look at how Chorus.ai uses AI differently from most: "For starters, the system was built around one main goal – business. Speaker recognition, recognizing pain points and keeping an accurate log of conversations were the biggest components of that goal. To that end, Chorus.ai ordered specially modified GPUs made for the sole purpose of running intensive AI training operations. Deep learning, a core AI technology, is at the core of most of what Chorus.ai does. The company’s natural language processing systems work in concert with a language model and optical character recognition for video calls, giving the system multiple ways to figure out who’s speaking, what they’re saying, and most importantly – what it means in context. When the product hits a client’s servers, it automatically starts building up a database of that client’s conversations, related jargon, and common repetitions."

• Serbia/Startups. The NYT on how Serbia is turning to tech startups to combat economic stagnation: "While a small player in global or even Western European terms, Serbia now generates 10 percent of its gross domestic product from information technology."

• UK/Fintech. Previse raised $7M for an ML-based platform to accelerate SMB payments. Notably, investors included Bessemer.

• The startup nation grows up and focusses. Data continues to reveal a slowdown in new company formation in Israel: "The Startup Nation has seen a dwindling number of startups founded over the past few years, from over 1,000 in 2014 to 700 in 2017, according to a new report on the Israeli tech ecosystem released this month by Start-Up Nation Central (SNC)."

Worth reading

• And the money kept rolling in. The NYT on the ever more frequent "mega-round:" "Annie Lamont, a managing partner at the venture fund Oak HC/FT, expected a drop-off in start-up valuations and funding three years ago, but it never happened. Now, she expects more of the same, partly because most the companies can easily get more money and few are worried about a downturn. “The fear of a correction is not occurring,” she said. If any start-ups do “vaporize,” she said, “I think people are going to ignore them and roll right on to the next one.”"

• The AI playbook for minimal algorithmic performance (MAP). Zetta Venture Partners' Ivy Nguyen offers a playbook for efficiently testing an AI-based approach to most problems: "The best AI startups we’ve seen figured out as early as possible whether they were collecting the right data, whether there was a market for the AI models they planned to build, and whether the data was being collected appropriately. So we believe firmly that you must try to validate your data and machine learning strategy before your model reaches the minimal algorithmic performance (MAP) required by early customers."

• GraphQL in the enterprise. Stackshare on how big companies are starting to deploy GraphQL.

• Conversational AI. Datanami reports on the mainstreaming of this trend, with Gartner expecting that by 2020 customers will manage 85% of their interactions with companies without interacting with a human. 

• Digital Health Revenues. Some (rare) revenue data from 59 digital health startups.

• Kara Swisher on Drugs. The storied tech journalist on "How and Why Silicon Valley Gets High."  Now I understand why I'm not getting anywhere... 

Portfolio News & Jobs

A look at how Chorus.ai uses AI differently from most: "For starters, the system was built around one main goal – business. Speaker recognition, recognizing pain points and keeping an accurate log of conversations were the biggest components of that goal. To that end, Chorus.ai ordered specially modified GPUs made for the sole purpose of running intensive AI training operations. Deep learning, a core AI technology, is at the core of most of what Chorus.ai does. The company’s natural language processing systems work in concert with a language model and optical character recognition for video calls, giving the system multiple ways to figure out who’s speaking, what they’re saying, and most importantly – what it means in context. When the product hits a client’s servers, it automatically starts building up a database of that client’s conversations, related jargon, and common repetitions."

Datos is hiring a BD lead in the US.

Moltin is hiring for multiple roles in the US and UK.

Resin is hiring globally.