Ra'anana-based Anodot has completed its B financing round, in which it raised $23 million. The round began last September, when the company raised $8 million, and it has now added $15 million to that amount. Anodot has now raised a total of $26.5 million since it was founded in 2014. Redline Capital Management led the additional investment, with participation from the Aleph Venture Capital and Disruptive Technologies Venture Capital funds.
Anodot has developed an analytics platform based on artificial intelligence used by nearly 100 customers, including Comcast, Microsoft, Wix.com Ltd. (Nasdaq: WIX), Waze, AppNexus, AOL, and LivePerson. The company has 45 employees, including 28 in Israel and the rest in the US and a small office in Australia. Following its financing round, Anodot plans to also open an office in London and substantially boost its sales volume in the US, and to increase its staff to 100 by the end of next year.
CEO David Drai, chief data scientist Ira Cohen, and VP R&D Shay Lang founded Anodot. Drai was a cofounder of Cotendo, sold to Akamai in 2012 in a deal estimated at $300 million, and was later technology manager at Gett. Lang has served in senior development positions, including at Finjan and Chicago-based security company Trustwave, which acquired M86 Security, where Lang was development manager. Cohen was a senior researcher and information scientist at HP, after completing an MSc in electrical engineering and computers at the University of Illinois.
Drai said, "We've been selling the technology for two years already, and tripled our revenue last year with sales of several million. The technology itself is agnostic; we adapt it to anyone who has a very large amount of data. It doesn't matter whether it's adtech or fintech or the industrial Internet of Things (IoT). We're able to derive insights."
"Globes": What distinguishes you from other technologies?
Drai: "The conventional business intelligence market, which totals $20 billion annually, usually uses visualization, a dashboard, to detect what is happening with revenue, the number of users, repeat users, how many of them paid and how many didn't, and so forth. When you accumulate more data, it becomes difficult to keep track of everything that is happening in your business world. For example, if you want to know now the state of sales in Tokyo for iPhone users, the resolution is such that the human eye starts having trouble following these dashboards and extracting insights from them. It certainly can't be done in real time.
"Our system learns all the data in real time. Instead of being a platform for questions, we're a platform for answers. We surface all the insights we discover, and ask the customers what interests them. Are they interested in revenue? Something practical like the waiting time for loading the website? As soon as they tell us what interests them at the macro level, we surface all the insights related to the subject at the lowest resolution there is, and when something exceptional happens, whether good or bad, we're able to say not only what's happening, but why it's happening. We provide the story behind the change.
"In spheres in which there is a great amount of data, one of the headaches is seeing what happened in time. Another one is investigating it and understanding what happened. We do this in almost no time, and that improves revenue very nicely. We have a customer whose revenue we improved by several million dollars. For example, if I find a drop in revenue from iPhone users in Russia, say because there is a bug in the new version that came out in Russia, I'll bring it to the surface before it becomes really bad.
"In adtech, for example, we can detect a decline or halt in purchases of advertising space. This makes it possible to find out the reason for it. In fintech, for example, there is the problem of payments. You work with a credit card and receive rejects of a card, and by the time you find out about it, you have already lost a lot of money. This month, there was a major incident at Macy's, which rejected credit cards for six hours because of Black Friday. This is enormous damage, which we make it possible to detect in real time
"In industrial IoT, we have a large auto manufacturing customer, and there is a customer who manufactures industrial printers. There it starts with the temperature of the printer. If there is a deviation in the temperature of some component in the printer, excessive consumption of ink, or in cars it can even be at the level of reinforcement of screws, if the pressure on a screw suddenly deviates from the norm. We're able to issue an alert about it at the production stage."
It sounds like installing the technology with each customer takes a long time. The software has to be adapted to different applications.
"Not necessarily. What we have developed are 'collectors.' In most workplaces, information is gathered in standard places, whether cloud servers or standard databases. We have developed collectors that take the data from these places and send the information continuously."
For how long is the financing round?
"Our plan is to build something with a presence. We're not looking for a quick exit. The business plan is to triple revenue next year as well, and this money will last us for about two years, assuming that we fulfill the plan."
Will you hold a Nasdaq IPO after that?
"No. We have to increase revenue a little more before an IPO. We're too small to talk on that scale now."
Published by Globes [online], Israel Business News - www.globes-online.com - on December 20, 2017
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