New York funding news: Software and artificial intelligence top recent local investments

New York-based customer service company Catalyst Software has secured $15 million in Series A funding, according to company database …

New York-based customer service company Catalyst Software has secured $15 million in Series A funding, according to company database Crunchbase, topping the city’s recent funding headlines. The cash infusion was announced July 30 and led by Accel.

According to its Crunchbase profile, “Catalyst develops an intuitive Customer Success Platform (CSP) for customer sales teams, helping them reduce churn, drive product adoption and build customer relationships at scale.”

The three-year-old startup has raised two previous funding rounds, including a $3 million round in 2018.

The round brings total funding raised by New York companies in software over the past month to $500 million, an increase of $67 million from the month before. The local software industry has produced 547 funding rounds over the past year, securing a total of $8.8 billion in venture funding.

In other local funding news, employment and employee benefits company Harver announced a $15 million Series B funding round on July 31, financed by Insight Partners.

According to Crunchbase, “Harver is a pre-employment assessment platform for hiring at scale. Hundreds of the most innovative companies use Harver to digitally transform their candidate selection process and hire top talent.”

Founded in 2015, the company has raised four previous rounds, including a $4.2 million Series A round in 2018.


This story was created automatically using local investment data, then reviewed by an editor. Click here for more about what we’re doing. Got thoughts? Go here to share your feedback.

Related Posts:

  • No Related Posts

Cybereason Raises $200M Led By SoftBank, Continuing Cybersecurity’s Boom

Cybereason, a startup focused on you guessed it, cybersecurity, announced this morning it has raised $200 million from SoftBank Group and its …

Cybereason, a startup focused on you guessed it, cybersecurity, announced this morning it has raised $200 million from SoftBank Group and its affiliates. The company’s valuation is around $1 billion, though reports vary as to whether it’s a little less, or a little more than that figure.

Subscribe to theCrunchbase Daily

The company uses big data analytics to identify and handle cyber attacks. Specifically, CEO Lior Dov says the company’s mission is to help “security teams prevent more attacks, sooner, in ways that enable understanding and taking decisive action faster” with the help of AI.

Over the past two years, Cybereason said it has increased its customer base by 300 percent “with over six million endpoints under protection.” (In cybersecurity, endpoint protection refers to securing devices at the end of a network; laptops, tablets, mobile phones, and so forth. In a world of both big data and strengthening mobile networks, endpoint security is a natural growth industry thanks to the secular shifts towards greater data collection and retention, and an increasingly mobile workforce.)

Cybereason is based in Boston but has 500 employees working out of its home base and offices in Tel Aviv, Tokyo, London and Sydney, Australia. Israeli military veterans founded the company in 2012.

In its press release, Cybereason said it plans to use the new capital toward ramping up operations with an eye toward “global growth in all geographies.” It also wants to aggressively expand its partner program and improve upon its endpoint security product.

The company is tipped to be headed for the public markets. According to an interview with Forbes, Cybereason is looking at a public debut when “market conditions” line up. Of course, that’s what every company looking at going public that isn’t quite ready yet says, so it’s hard to draw too much insight from the statement.

Notable, however, is the scale of capital that Cybereason just raised. Indeed, the company’s prior total capital raised to date was about $189 million (Softbank led its 2015 Series C and its 2017 Series D, for reference.) That means Cybereason just raised more in its Series E than it had raised before, added together. Previous investors include CRV, Spark Capital and Lockheed Martin.

Here’s a look at its fundraising history to date:

The new capital will likely delay its IPO; perhaps Cybereason could have gone public inside the next few quarters if it needed to. But with $200 million fresh dollars sitting in its accounts, why would it? And that means a company SoftBank has poured capital into a number of times could miss the current IPO window, a winsome season that has seen companies of all levels of quality go public.

As a final bit of context, recall that cybersecurity is a hot sector. Crunchbase News reported a grip of funding rounds in the space and a recent IPO to draw attention to cybersecurity’s rise. Cybereason is part of the same wave. Expect more, related rounds in the coming months.

Illustration: Li-Anne Dias

Related Posts:

  • No Related Posts

Automated Machine Learning from DataRobot

Founded in 2012, Bahstun based startup DataRobot has taken in a total of $226.4 million in funding with $200 million of that closing just last week.

The notion of nanoscale self-replicating machines getting out of control and covering the earth in “gray goo” is an idea proposed by Eric Drexler in his 1986 book Engines of Creation. Similar to how cancer cells begin multiplying in an out of control fashion and wreaking havoc in a host organism, machines might be capable of doing something very similar – but with planet earth as the host organism. One mistake in the master control program and the nano-sized machines suddenly start replicating out of control using all the building blocks they can get their grubby little nano-paws on until there’s this giant puddle of grey goo that eventually coats the entire planet and we all die. Then, that Italian guy can stop asking “where are they” because we’ll have found at least one proven cause for “the Great Filter.”

While we may not have machines that are capable of self-replicating at that scale, we do have things like Robotic Process Automation (RPA) where the machines are learning how to behave like your average Mumbai back office worker. We’re now seeing code that codes itself. Machines that learn in an unsupervised fashion. And something called “automated machine learning.”

You know the old joke that people used to crack about how machine learning is like high school sex. Everyone talks about it, everyone says they do it because they think everyone else is doing it, but the reality is nobody’s doing it. Fast forward to today and everyone’s doing it and far too many people are talking about it. Anyone who uses basic Natural Language Processing (NLP) algorithms to screen scrape a few websites now claims to be using AI as a competitive advantage. AI has been commoditized, and anyone who doesn’t use AI is already being left behind. If you’re a CTO that thinks your company might be in that bucket, you need a quick low-risk fix so you can “fail fast” before bonus time rolls around. What you need to do is look for companies that are Making Artificial Intelligence Easy to Use. We wrote about three such companies, one being DataRobot.

The Growth of DataRobot

Founded in 2012, Bahstun based startup DataRobot has taken in a total of $226.4 million in funding that came from a slew of big names in the venture capital world along with corporate investors – chipmaker Intel and the third-largest life insurance company in the United States, New York Life Insurance. They’ve used all that money to build a platform which ingests your raw data which it will cleanse and subject to a multitude of algorithms before choosing the best one using – you guessed it – more AI algorithms. Now, here’s where we feel compelled to address the elephant in the room.

Everyone’s talking about a Series E funding round that supposedly took place last week in the range of $200 million but the company told us they haven’t said squat yet so that means nothing has actually happened. However, the geniuses at CB Insights have now valued the startup at $1 billion dollars giving them a spot on the CB Insights Unicorn List which now has 384 members. Since CB Insights is largely infallible, we’re not sure what to make of the whole thing except to say we’ll update this article when there’s more color around this mythical funding round.

With 472 open jobs right now, the company describes a “hypergrowth mode where groups within the company work like start-ups within the start-up.” That sounds about right considering they’ve been acquiring other companies as they go along. According to CrunchBase, they’ve now made four acquisitions. One we featured before – Nutonian – which made our list of 10 Data Science and Predictive Analytics Startups. Let’s talk about the other three.

When Startups Eat Startups

ParellelM

When a larger company acquires a smaller company, that’s the last chance you get to see what the smaller company was doing before everything goes behind the curtains. The most recent acquisition made by DataRobot was a startup called ParrellM which was founded in 2016 and had taken in an undisclosed amount of funding to “help their customers automate the deployment, scaling and ongoing management of ML services in production,” something they refer to as “MLOps.” That’s just a play on the term “DevOps,” something we talked about in our article on “Algorithmia – The World’s Biggest Algorithm Marketplace.” An Israeli tech news site, Ctech, wrote a piece about the acquisition titled “Disappointing Exit for Machine Learning Company ParallelM” which states that the “sum of the acquisition, which stood at several tens of millions of dollars, did not yield a return on investment for the company’s shareholder.” Sounds like DataRobot came ahead in that transaction.

Cursor

The second acquisition DataRobot made this year was a San Francisco startup called Cursor which was founded in 2017 and had taken in $2 million in funding. They’re now “part of the DataRobot family” which means their corporate website has disappeared and all that remains is a picture of the smiling founders who are probably thinking about which overpriced Bay Area property investments they plan to make with their newly acquired windfall. Press releases about the event say nothing of value, but rather make vague mentions of “quests,” “joining forces,” “unleashing value,” and “key pieces of the puzzle,” which is exactly why we try to avoid PR people like the plague. Best we can tell, Cursor was building a data collaboration platform which used AI algorithms to scour disparate data sources both internal and – and more recently external – to a firm. An article by Tech Crunch last year elaborates on this a bit:

Cursor more or less behaves like a search engine internally. Users can search for information, which will surface up anything from a Tableau worksheet to an actual segment of SQL. Users can then comment on the information coming up from those searches, which are tagged with metadata to help employees find that information more easily. The idea is that if someone over on one side of a production team needs something (like a segment of code), they should have some kind of intuitive way for finding it rather than having to start an email chain with dozens of people on it.

No mention was made of how much Cursor was acquired for.

Nexosis

The third acquisition took place in 2018 – the only acquisition that year – and involved an Ohio startup called Nexosis that pulled out of the public’s view so fast that their domain is now for sale. Founded in 2015, Nexosis had taken in $7 million in funding to develop “a machine learning API for developers that featured automatic data processing, model selection, and multiple time series specific algorithms,” according to CB Insights. Said Jeremy Achin, CEO and Co-Founder, DataRobot:

Other companies in the data ecosystem looking to try to copy DataRobot should seriously think about firing their corporate development people for missing an opportunity like this.

Looks like DataRobot knows where to find value. Now, let’s look at what they’re doing with all this firepower.

Automated Machine Learning

The idea behind automated machine learning is exactly what it says on the tin. Companies have tons of data lying around in disparate systems and they want to extract insights from that data that they can use to create efficiencies which generate more profits for shareholders. More than 3,100 companies have used DataRobot’s automated machine learning platform to build 1,268,134,812 models – so apparently, it scales really well.

Here’s a look at just a few of the wide variety of use cases for automated machine learning. (By the way, if your company has a Marcoms team, make them spend a good chunk of their time putting together case studies because it helps these articles write themselves.)

  • Concert Tickets – The marketing team at DR Koncerthuset sold 83% more tickets when emails were personalized and sent to specific subscribers that DataRobot predicted would buy tickets to particular events.
  • Kobe Bryant – Sports is largely the opiate of the people, particularly for the Americans who have a bunch of sports the rest of the world largely doesn’t care about. In America there’s this guy who plays basketball called Kobe Bryant and someone used DataRobot to analyze all 30,699 shots he took. You can read about it here if that’s your cup of tea.
  • Supply Chain Models – Lenovo – big Chinese firm that sells $45 billion worth of computing stuff a year – needed to predict sell-out volume among their retailers using 59 variables. Creating a single model took 4 weeks to build and 2 days to deploy. With DataRobot, models were created in 3 days and deployed in 5 minutes – and accuracy increased from <80% to 90% today.
  • Water Availability – Using a database of half a million water points around the world, a nonprofit was able to predict which water points were likely to break in the future.
  • Oil Drilling – Used to analyze core samples taken from oil wells and predict where recoverable oil or gas is likely to be.

As you can see, if you have data from nearly any domain then DataRobot can extract useful insights from it. You don’t need to hire a team of data scientists in order to casually mention in the next board meeting how you used machine learning to extract some grand insight from your company’s data.

Competition

Before we wrap this up, it’s useful to see who else is dabbling in this space. Research firm Gartner puts together these “magic quadrants” which are the sort of thing an MBA might hand you and walk away thinking they actually did something of value. The accompanying data in the report is decent, and it’s good for letting us know who else is playing in this space.

Magic Quadrant for Data Science and Machine Learning Platforms

Magic Quadrant for Data Science and Machine Learning Platforms – Source: Gartner

Some of the names in the above list could represent a future exit for DataRobot. Maybe IBM can sort something out because the growth in our quarterly dividend checks need to come from somewhere and it’s not looking like Watson will be the source of that growth though we could be wrong. Here’s a blurb from that report on how DataRobot’s aforementioned acquisitions have helped them become a leader in this space:

DataRobot sets the standard for augmented data science and ML. Significant funding has enabled expansion via acquisitions to address time series modeling (Nutonian in May 2017) and an augmented approach for developers to incorporate models into applications (Nexosis in July 2018). These acquisitions give DataRobot the opportunity to extend its capabilities to new types of user, while focusing on its core competency of augmentation.

It then goes on to mention that DataRobot is quite pricey – but you get what you pay for, right?

Conclusion

One mistake that newbie investors make is to look at their portfolio too often. Every time a stock price fluctuates by more than 3% on a given day, they’ll panic and begin to question their investment decisions. While the “set it and forget it” approach has its downsides – at least when it comes to the fast-moving world of tech investments – there’s a certain advantage you gain by looking at a company every several years and assessing their progress. Since we first looked at DataRobot over two years ago, they appear to be moving away from the pack and successfully scaling. Fresh funding means they can now fill some of those open job requisitions through “aqui-hires” as opposed to waiting for the recruiting department to win the “the war for talent” – a phrase some PR person came up with to describe the act of persistently pestering people on LinkedIn.

Looking for lower transaction costs? Zacks Trade is offering $1 trades for U.S. stocks and options. for one year after you open an account. After a year of dollar trades, you’ll pay just $3 a trade or a penny a share, whichever is greater. Zacks Trade is one of the cheapest brokers out there and we use them to trade stocks on over 90 foreign stock exchanges. Click here to open an account.

Related Posts:

  • No Related Posts

Glyph nets $150000, plus more top funding news for New York-based companies

New York-based shoes company Glyph has secured $150,000 in seed funding, according to company database Crunchbase, topping the city’s recent …
<p>Photo: Glyph/<a href="https://www.facebook.com/glyphshoes/photos/a.255058041908246/358366528244063/?type=3&theater" rel="nofollow noopener" target="_blank" data-ylk="slk:Facebook" class="link rapid-noclick-resp">Facebook</a></p>

Photo: Glyph/Facebook

New York-based shoes company Glyph has secured $150,000 in seed funding, according to company database Crunchbase, topping the city’s recent funding headlines. The cash infusion was announced July 22 and financed by 500 Startups.

According to its Crunchbase profile, “Glyph is a startup that specializes in developing digitally knit shoes. It aims to develop products that are non-animal-based. Glyph was founded in 2017.”

The two-year-old startup also raised a convertible note round in 2017.

The round brings total funding raised by New York companies in manufacturing over the past month to $29 million. The local manufacturing industry has produced 26 funding rounds over the past year, raking in a total of $149 million in venture funding.

In other local funding news, tourism company CLEAR announced a corporate round on July 29, financed by United Airlines.

According to Crunchbase, “CLEAR makes it simple to be you, by using biometrics to build a connected world that’s smarter and more secure. Our platform instantly connects your life from airports to arenas.CLEAR powers secure, frictionless customer experiences at more than 30 airports and stadiums nationwide, and so much more to come.”

Founded in 2010, the company has raised four previous rounds, including a round earlier this year.

Meanwhile, developer platform and open source company Blockstack raised corporate round funding, announced on July 25. The round’s investors were led by SNZ Holding.

From the company’s Crunchbase profile: “Blockstack is a decentralized computing network that puts users in control of their data and login. It’s the easiest way to build decentralized apps that can scale. Blockstack enables engineers to build secure, privacy-focused applications. Users are in control of their data instead of storing it with large tech companies.”

Blockstack last raised $12 million in an initial coin offering earlier this year.

This story was created automatically using local investment data, then reviewed by an editor. Click here for more about what we’re doing. Got thoughts? Go here to share your feedback.

Related Posts:

  • No Related Posts

DataRobot and PathAI top Boston’s recent funding news

Boston-based predictive analytics company DataRobot has secured $200 million in Series E funding, according to company database Crunchbase, …

Boston-based predictive analytics company DataRobot has secured $200 million in Series E funding, according to company database Crunchbase, topping the city’s recent funding headlines. The cash infusion was announced July 29 and financed by Sapphire Ventures.

According to its Crunchbase profile, “DataRobot offers a machine learning platform for data scientists of all skill levels to build and deploy accurate predictive models in a fraction of the time it used to take. The technology addresses the critical shortage of data scientists by changing the speed and economics of predictive analytics.”

The seven-year-old company has raised seven previous funding rounds, including a $100 million Series D round in 2018.

The round brings total funding raised by Boston companies in artificial intelligence over the past month to $214 million, an increase of $200 million from the month before. The local artificial intelligence industry has seen 51 funding rounds over the past year, yielding a total of $692 million in venture funding.

In other local funding news, health diagnostics company PathAI announced a corporate round on July 24, financed by LabCorp.

According to Crunchbase, “PathAI’s services solve the most challenging pathology problems faced by the research and pharmaceutical industry. The PathAI platform provides end-to-end automation for reliable, scalable and cost-effective long-term solutions. Their solutions make discovery scalable.”

Founded in 2016, the company has raised three previous rounds, including a $60 million Series B round earlier this year.


This story was created automatically using local investment data, then reviewed by an editor. Click here for more about what we’re doing. Got thoughts? Go here to share your feedback.

Related Posts:

  • No Related Posts