FREMONT, Calif. -- Procera Networks, Inc. (NASDAQ: PKT), the global intelligent policy enforcement company, today announced that a large telecommunications equipment manufacturing (TEM) company has licensed Procera's Network Application Visibility Library (NAVL) Deep Packet Inspection (DPI) engine, designed to provide their customers with comprehensive application classification technology to enhance their monitoring and testing applications. Procera expects to recognize the revenue from this contract over the next three years.
"This implementation has the potential to be one of many with this TEM. We are pleased to continue our success providing solutions to telecommunications equipment manufacturers," said Jason Richards, senior vice president of Business Development at Procera. "We see a growing demand for Intelligence Everywhere, and network operators are looking for DPI solutions that enable them to have greater visibility and control of their networks."
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A recap of the week's talking points on Light Reading's sister site, telecoms.com. Facebook AI programmers had a bit of a brain-fade as they allowed one of its AI applications to invent its ...
In case you missed it, Amazon's 1% stock increase helped Jeff Bezos dethrone Bill Gates as the richest man in the world. Also, Taiwanese electronics manufacturer
At an event in Wembley stadium, EE used its live network to demonstrate gigabit LTE using a Sony Xperia XZ Premium smartphone with a Qualcomm Snapdragon 835 chip.
Guavus unites big data and machine intelligence, enabling many of the the largest service providers in the world to save money and drive measureable revenue. Learn how applying Machine Intelligence substantially reduces operational costs and in many cases can eliminate subscriber impact, meaning a better subscriber experience and higher NPS.
When used to analyze operational data and to drive operational decisions, machine intelligence reduces the number of tasks which require human intervention. Guavus invested in Machine Intelligence early. Learn about the difference between Machine Learning and Machine Intelligence.
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Understanding the full experience of women in technology requires starting at the collegiate level (or sooner) and studying the technologies women are involved with, company cultures they're part of and personal experiences of individuals.
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