Definitely, if new artificial intelligence (AI) startup 3TEB8 has anything to do with it. The company’s just managed to secure $2 million in seed funding in a round led by Social Capital in conglomeration with other investors including Amr Awadallah (founder and CTO of Cloudera), 500 Startups, The Alchemist accelerator, and Citrix.
“The experienced team at 3TEN8 is combining their deep domain knowledge of telecom network operations with advanced AI and machine learning techniques in a way that completely disrupts how we think about network operations and efficiency,” said Awadallah. “With laser-like focus on the subscriber’s experience on the network, 3TEN8 doesn’t just diagnose and predict degradations and failures, they automate prioritisation for carriers so that resources are efficiently allocated to maximise the subscriber’s overall experience, thus minimizing long-term churn rates.”
3TEN8 is capable of predicting future network states as many as 72 hours in advance. This includes traffic patterns and congestion as well as the health and performance of the network. The AI technology can diagnose anomalies in the network with an accuracy of around 90%. This saves engineers a great deal of time troubleshooting, therefore reducing overall costs for the business.
“As increased data usage from high bandwidth puts pressure on wireless networks, carriers’ operational expenditures are rising and margins are shrinking,” said co-founder and CTO of 3TEN8, Miro Salem. “Recent advances in artificial intelligence, cloud computing, and new 3GPP 5G Protocols have enabled us to develop a proactive system that will automate 90% of wireless network operations. We welcome Macros to the company, as his expertise will help our team move the industry into a more intelligent, AI-guided operational model.”
Marcos Perreau Guimaraes has a background that features both data analytics and machine learning working at Stanford University and Inria as a researcher and Principal Investigator. He now joins 3TEN8 as Chief Data Scientist and VP of Machine Learning engineering. “I am thrilled to join a team that is disrupting the status quo in an industry that is ripe for more efficient operations,” said Marcos. “We are analyzing weather, public events, topography and landscape, geolocation, configurations, alarms and faults on the network, and overall performance to predict when and where there will be network anomalies, and beyond prediction we provide diagnostics that do not need to be programmed by engineers, increasing customer satisfaction and reducing the industry’s dependence on antiquated and costly vendors.”