Combining Word-Class Machine Learning With Financial Services Expertise
Our mantra at Work-Bench, which you can see printed in vinyl right when you enter our workspace, is that great things happen at the intersection of suits and hoodies.
I don’t think that a company of ours has ever better exemplified this more than Merlon Intelligence, which is why we’re thrilled to announce that Work-Bench is joining in their $7.65M raise led by Data Collective with participation from Fenway Summer and Nyca Partners.
Too often companies from the Valley and beyond approach Wall Street thinking that they can solve their problems better, faster, and cheaper, however they usually lack the necessary context and domain expertise to fully appreciate the problem at hand (including existing tooling and workflows).
When we come across those rare founders who have an extraordinary vision for how the world should be and who pair it with deep customer empathy and an ability to execute, it gets us excited.
Such is the case with Merlon Intelligence, where one day last year we got a call from someone at a bank we work closely with, who said that we had to check out an incredible new startup solving Anti-Money Laundering (AML) and Know Your Customer (KYC) compliance unlike anything they’d seen before in the market.
The other day I received an email from a CEO within our Work-Bench community:
“Even though we are still tiny, as we evolve our team and employees begin to grow into management roles for their first time, I’ve started to think a lot about management training. As a first time CEO, this is definitely new territory for me as well.”
This is one of the most common painpoints I hear, across the fastest growing VC-backed enterprise startups we work with and the globally distributed Fortune 1000 corporations in our corporate network: managing people is hard.
And yet there are still surprisingly few technology products that have served this people manager and leadership development training space, estimated to hit $13.8B in 2020 (here), which to date still revolves largely around in-person trainings and workshops.
Given the rise of AI across a range of verticals: financial services, life sciences, healthcare, energy, transportation, heavy industry, agriculture, and materials — we have yet to see AI broadly applied to the people manager training space (though there are some early startups tackling this space, as detailed in my slides above).
Last week, startups, corporates and academia braved a Nor’easter to attend Spark Summit East in Boston. Spark is an open source, big data processing engine originally developed at Berkeley’s AMPLab by Matei Zaharia. Used behind the scenes at some of the largest data applications at web scale companies, Spark makes data analytics fast. Today, we’ve reached a pivotal moment where forward thinking enterprises like Capital One, Walmart Labs and others are working with Spark to better serve their customers. This post will explore key takeaways from Spark Summit, while providing details on the leading use cases and companies in the emerging ecosystem.
The most successful businesses over the next decade will deliver highly personalized experiences for their customers, powered by advanced streaming analytics. A key theme seen in a number of companies both presenting and exhibiting at Spark hinted at a common goal: building a best in class data pipeline to run models easily and securely. Webscale companies have robust data management practices through in house systems and a combination of open source and commercial tooling. This is, however, a gargantuan undertaking for a large enterprise and something that even the most forward thinking corporates are keen on setting up. Several of the attending startups - like Streamsets, Kofa, and Qubole - attempt to address this.
Last week in Tel Aviv was a big moment for Israeli cybersecurity. CyberTech Israel, boasting over 10,000 attendees from five continents, quickly established itself as one of the de facto conferences outside of the United States. CyberTech was comprised of the usual conference features: talks, panels, swag, and famous speakers. However, what makes the conference really standout is its access to the latest crop of early stage startups. According to Start-Up Nation Central, total investments in 2016 for the Israeli cybersecurity reached $581 million, an increase of 9 percent over the previous year. Israel’s Prime Minister Benjamin Netanyahu even made an appearance, marking the importance of cybersecurity to Israel and the nation’s identity.
Israeli cybersecurity prominence isn’t new - Check Point and CyberArk are well known and leaders in their respective fields, and you don’t have to look far to find Israeli talent present in other security firms. The blend of military conscription and Israel’s place as a cyberwarfare superpower has helped to create a steady output of innovation and talent. Israeli entrepreneurs are translating the skills and abilities they honed in their IDF service into technologies for the market, giving organizations a view into the bleeding edge in cybersecurity.
Using data from the Enterprise Startups Funding Database - where every week we track and record all publicly announced enterprise technology funding rounds - we took a look back at 2016 to see how it stacked up against 2015 and 2014.
In line with holistic 2016 trends we’ve seen from Pitchbook and Fortune, 2016 was a year where the market normalized. This makes sense after a record breaking 2015 with close to $15.8B invested across 648 enterprise deals - a nearly 82% and 75% increase over 2014 totals, respectively. Building on our analysis of the first half of 2016, here's what we saw:
Compared to 2015, enterprise funding decreased by 20% in 2016, with $12.6B deployed in the year. However, deal count only dipped 6% to 611 financing events in 2016 vs 648 in the prior year.
Later Stage financing bore the brunt of the decreased capital deployment, with the share of Series D (and later) rounds across the country falling to 9.2% of total deal volume compared to 13.3% in 2015.
New York is still solidly in command of second place for enterprise software. In total since January 2014, New York has seen $3.9B flow into various enterprise startups over a total of 222 financings.
Although 2016 saw a drought of IPOs, it was a stellar year for enterprise M&A with over $65B in acquisitions.
See below a full breakdown of our research highlighting the key activity underpinning this movement, and if you’d like to get in touch, please feel free to shoot us an email or reach out via Twitter to @Work_Bench.