In the rapidly evolving landscape of software development, the transition from DevOps to DevSecOps has emerged as a strategic imperative. While DevOps has proven instrumental in fostering collaboration between development and operations teams, the integration of security into this paradigm becomes paramount to address the escalating challenges posed by cyber threats and compliance requirements.
We have built several solutions for telecom operators to minimize value at risk, optimize their tariff portfolio, uplift customer base and maximize converged foot-print. Our machine learning models are extended across various functional units including marketing, network operations and finance, in the domain of telecommunication.
We offer several scientific models to estimate consumption demands based on the consumption data of individual customers and fuse it with various pricing schemes that the distribution companies use for billing purposes and accordingly propose an efficient energy management scheme for that distributor.
As more and more organizations are practicing data-driven culture, the wheel of data science processes is getting more elaborative. In addition to the classical components of the data science execution model highlighted in green, the need for bias detection, correction, and explainable AI has become evident. Just like bias in the models can lead to lethal consequences, providing just the probabilities of a phenomenon is not longer sufficient as it have become equally important to understand the rational behind every recommendation.
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