That said, it can be challenging for companies transitioning from traditional networks to SDN and integrate network functions virtualization (NFVs) or virtual network functions (VNFs) without the risk of disrupting support services and impacting the end-user experience. “With an increase in microservice-based applications, as well as highly distributed dynamic architecture, we realized that customers with traditional legacy systems are experiencing data volume problem that make end-to-end management more difficult,” explains Drew Golden, Sr. Director of Product Management at Federos. In a bid to address the significant gap and shortcomings, Federos offers, Assure1®, a carrier-grade, software-defined service operations platform designed to simplify and modernize legacy solutions with machine learning and support the transition to an AI Operations-based infrastructure. The company helps service providers and carriers simplify, automate, and transform their network operations centers by cutting complexities associated with end-to-end service management.
“Our solutions are designed to provide businesses the ability to transform their IT operations from being a traditional cost-center into a data analytics-based continuity service for consumers,” states Golden. As part of its customer satisfaction methodology, Federos’ consultants conduct an assessment of the client’s current operational situation, workflow processes, and operational core objectives before the implementation of Assure1®.
Federos leverages AI and machine learning to provide real-time operational intelligence that enables companies to maximize the uptime of critical networks and services and continuously improve business performance
Once deployed, the company’s platform uses AI/ML for rapid and accurate identification of root causes in real-time, reducing service outages and minimizing the impact on the customer experience.
Designed to be open, multi-tenant, and highly scalable, the solution is ready to address current and future needs of service providers seamlessly and runs with existing legacy systems. Federos’ hyperscale platform unifies data from various disparate sources of a client’s network to normalize it into a standard object model and run effective machine learning algorithms for advanced correlation and causality– RCA3 – , prediction, and automation that provide actionable insights with customizable reports, dashboards, and portals. By leveraging real-time inputs and cross-domain analytics, users can trigger zero-touch or closed-loop automation of proactive recovery actions to address the fundamental problems of ‘swivel-chair’ operations spanning multiple systems and customer databases. The platform also features an extensive library of supported network devices, and certification of new devices takes a fraction of the time taken in legacy platforms.
With the surge in demand of firms seeking to leverage artificial intelligence and machine learning as a competitive edge to secure the future success and scalability—Federos’ has had the prescient to stay ahead of the curve. The company provides customers with monthly updates of the platform to enable them to mitigate present challenges and adapt to future requirements—while ensuring zero downtime. “We view artificial intelligence as the next big step in the market. Federos leverages AI and machine learning to provide real-time operational intelligence that enables companies to maximize the uptime of critical networks and services and continuously improve business performance” concludes Keith Buckley, Federos CEO.