Austin—[Updated 6/26/17, 9:55 a.m. See below.] SparkCognition, a company that uses machine learning software to monitor clients’ infrastructure and technology for malfunctions and other problems, has boosted its Series B round of funding to $32.5 million. The round was led by Verizon Ventures, the venture capital arm of telecom company Verizon. The company had previously announced a $6 million Series B in 2016, in which Verizon Ventures participated, but is now considering that a part of its Series A round.
Aerospace giant Boeing also is contributing to the funding through Boeing HorizonX, the company’s investment and commercialization division, along with some of SparkCognition’s previous investors. SparkCognition is using the money to add more customers—it says it has dozens of Fortune 100 and Fortune 1000 companies as clients—and to better develop its artificial intelligence and machine learning capabilities. [First paragraph updated to clarify that SparkCognition has now made its 2016 $6 million round of funding a part of its Series A round.]
SparkCognition’s artificial intelligence system analyzes data it collects from clients’ infrastructure and equipment, such as a turbine or a computer system in a centrifuge, and monitors it for abnormalities. For physical equipment that might not be internet-connected, SparkCognition collects data from sensors on the machines to monitor them. The software does the same with data from IT or internet-connected devices, watching for patterns that could mean an error is going to occur or some type of hack already has happened. [Updated to provide a new example of the system’s use.]
Since it was founded in 2014, SparkCognition has previously raised $16 million from a list of investors that includes Michael Dell’s private equity arm, MSD Capital, The Entrepreneur’s Fund, Alameda Ventures, Verizon Ventures, CME Ventures, and Brevan Howard, according to a press release.
A similar technology in San Antonio received grant funding earlier this month. Abdullah Muzahid, an assistant professor of computer science at University of Texas at San Antonio, was awarded a $450,000 grant from the National Science Foundation to further develop a hardware-based artificial intelligence system that can detect when software has bugs or a computer system has been hacked.
With the five-year grant, Muzahid and a group of students are developing an artificial neural network they are calling “NFrame,” a piece of hardware that can be plugged into computer systems, such as servers, to monitor data for abnormalities. Muzahid said in an interview that the value of having a hardware-based neural network is that it can operate and process data at dramatically faster speeds than software.
“In an ideal world, we will one day be able to have adaptive artificial neural networks like NFrame on every computer system to help it protect itself from software bugs and other risks that can make it vulnerable to attack or intrusion,” Muzahid said in a press release.
In other Texas funding news, another Austin-based startup, GenXComm, closed a seed round of financing last week, bringing its total funding to $1.5 million. The seed round was led by FAM Capital Partners, with other investment coming from UT Horizon Fund, among other unnamed investors.
GenXComm, which was founded last year, has developed a wireless technology that reduces interference in transmitters of 5G mobile, Wi-Fi, and cable networks data, enabling multiple transmitters to operate near the others, the company says.
“There is an immediate opportunity to dramatically enhance the user experience in key markets by leveraging GenXComm’s innovative simultaneous self-interference cancellation technology,” Sriram Vishwanath, co-founder and President of GenXComm, said in a press release.
The company, which was developed at the University of Texas at Austin, plans to use the money to make new hires and commercialize its technology.
