A the D11 conference in May, GE CEO Jeff Immelt outlined a vision for an “industrial Internet,” in which companies like his are turning to software to become more efficient. In particular, GE is especially enamored with Big Data, which can help the company anticipate industrial equipment maintenance needs.
GE is so serious about Big Data, in fact, that it is investing hundreds of millions of dollars in Big Data initiatives. It got the ball rolling on that in April with a $105 million investment in platform-as-a-service company Pivotal, and in June it launched its own analytics platform, called Predictivity.
Now GE has taken another step towards its “industrial Internet” goal by taking a stake in Big Data startup Ayasdi, which today announced a $30.6 million Series B round of funding. Joining GE in the round is Citigroup’s Citi Ventures, and Institutional Venture Partners, who led the round. Existing investors Khosla Ventures and Floodgate also re-upped.
Ayasdi started life in 2008, but it spent its first four years working mainly on US government contracts for the Defense Advanced Research Projects Agency (DARPA), and the National Science Foundation (NSF). A result of a decade of research at Stanford University, Ayasdi prides itself on being able to interrogate large and complex data sets without anyone having to query the data – in other words, you don’t need to ask any questions of a data set to find out interesting stuff. To achieve those results, it relies on machine learning and “topological data analysis,” which, very roughly speaking, looks for and “measures” shapes within data sets. One of Ayasdi’s most pronounced successes to date has been discovering a previously undetected type of breast cancer.
Ayasdi has come out to the open market at just the right time, capitalizing on a second wave of Big Data in which tech companies and startups are beginning to make Big Data more accessible and understandable to businesses and individuals, just as companies like GE are betting big on its future. An acknowledgement of the same trend is the reason why Accel Partners last month launched its second Big Data fund, worth $100 million. While it closed a $10.3 million Series A round only in January, the same time it came out to the public, Ayasdi already has clients such as GE, Citigroup, Merck, Mount Sinai Hospital, and the Food and Drug Administration.
As Immelt described at D11, the application of Ayasdi’s technology, which is available on the public or private cloud, can result in great efficiencies. A GE jet engine, for instance, has about 20 sensors that capture data in real time, Immelt said on stage. If the company can monitor and act on that data to, for example, save an airline 1 percent in fuel burn, it represents a saving of hundreds of millions of dollars.
Ayasdi CEO Gurjeet Singh says his company can automate insights from data when a data scientist isn’t available. “Using our platform, a lot of people can be converted into data scientists,” he says. But that doesn’t mean data scientists will be made obsolete by the technology. “The need is so large that you’re not going to see a reduction in the need any time soon, but it’s certainly the case that [companies using the tech are] going to amplify the efforts of data scientists they have on staff.” Ayasdi’s goal, meanwhile, is to automate the process of discovering insights to the point where it takes no time at all, says Singh.
Singh says the company decided to raise such a big round because of intense interest from investors, and because the business has been growing much faster than anticipated. In effect, the $30.6 million raise serves as a Series B and a Series C all at once, meaning the company might not have to raise more money in the future. Ayasdi will use the money to double its headcount from 50 to 100 people within a year, Singh says, in part to manage the volume of incoming leads. “We haven’t had enough people on the staff to answer the phones.” Including DARPA grants, Ayasdi has now raised a total of $44.6 million.
It will also use the money to further develop its tech as a product, and to automate its machine-learning techniques, so that it requires less service work and is more scalable.
Ayasdi also announced today that it is partnering with Cloudera, a Big Data platform that will work with Ayasdi’s app and machine-learning algorithms to facilitate the faster delivery of insights gleaned from data sets.
Now you have to count Ayasdi alongside a slew of others – including Platfora, Domo, Wibidata, DataGravity, DataStax, and Sumo Logic – in the forefront of Big Data’s second wave.