Companies must dispense with a siloed approach to product management and aspire for an integrated support system to address the above challenges. A cost-effective, efficient and responsive product sustenance engineering practice must leverage technologies such as product intelligence, Big Data, and analytics to reduce time to market. From independent software vendors and telecom leaders to aerospace and medical OEMs, optimized product sustenance engineering system finds strategic application across several industries. We use cutting edge tools to streamline the ISE solution process. Empowered by proven analytics-driven algorithms, our approach, couples data extraction/mining with software engineering best practices.

Approach

Our approach is centered around understanding product sustenance data from existing toolsets, people, process and knowledge pieces, and create actionable insights on the same.
Understand Product Sustenance Data >>>Establish Relationships and standardize these data pieces>> Suggest & Implement models based on Insights needed>> Ensure fundamental shifts in “Processes” & People practices

The solution that lies at the centre of our approach is iSE(Intelligent Sustenance Engineering)- software engineering domain’s first analytics based offering which harnesses the power of analytics driven algorithms to transform sustenance and testing lifecycle. It uses machine learning and text mining to improve sustenance activities such as source code analysis, defect fixing and test recommendation. eg. A leading telecom provider achieved 23% reduction in defect occurrence utilizing Intelligent Sustenance Engineering for code analysis, defect pattern identification, and discovery efficiency mapping.