CrunchMetrics is an advanced aberration detection system that was designed to help organizations identify business opportunities and reduce risks in real-time. The solution makes use of the combined power of statistics, Machine Learning (ML), and Artificial Intelligence (AI) to surf through data and identify abnormalities present in an enterprise. Subex is a leading telecom analytics solution provider, and the new brand launched by the company aims to assist users for various cases like retail, telecom, and fintech verticals at launch. CrunchMetrics is a wholly owned subsidiary of Subex Limited, and it is a division of Subex Digital LLP.

The colossal amount of data generated in the last decade is now produced within a few hours, and there is a massive rise in data volumes due to rapid civilization across various industries. Organization are doing well up to some extent in capturing and storing data, mechanisms make use of the large volume of data, but it finds difficulty in matching data volume generation with data velocity. This challenge has made organizations to fall short of response to these massive changes, and it fails to capture the chance to develop or improve business critical function. To eradicate the shortcomings and provide significant changes, CrunchMetrics provides real-time anomaly detection to help organizations to find even minor problems in colossus data and services, thereby assisting low abeyance decision making. By launching CrunchMetrics, Subex aims to undertake a vast market that has the potential to reach $4.5 billion by 2022, and it will reach out and cater to a variety of verticals.

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Vinod Kumar, CEO, and MD, Subex stated that the addressable problem and the market intensity are huge and they are determined to give value to customers. Two decades of handling large data has provided the company insights to manage a huge amount of data efficiently. It is becoming difficult to identify opportunities or foresight with contemporary business intelligence tool. The rule-based system is quite expensive for a few companies to adopt. An AI-based anomaly detection system can assist the users in making smarter decisions and saving time removing complexity. The automated solution will help the businesses identify incidents that are hard to detect, and through self-learning, the solution will evolve continuously.

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