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Infosys Live Operations
Infosys Live Operations is a smart platform for process excellence and deeper employee and customer engagement. It is a ‘system of systems’ that seamlessly integrates with legacy and digital environments to simplify operations by rationalizing applications and optimizing the technology stack.
Auto-discovery capability of the Infosys platform automatically executes events and activities, eliminating the need for permutation configuration of systems for every new occurrence in real-time production workflows. Further, reference data for all levels of activities and events needs to be defined only once, and not for every occurrence in a process or workflow.
The smart platform addresses the limitations of legacy BPM solutions by supporting operations and customer service delivery across multiple stacks. The modular system acquires, correlates, and analyzes data from existing BSS and OSS applications, including customer relationship management, activation / fault / performance management, and service assurance. In addition, it automates error redressal and communication within a workflow.
Infosys Live Operations platform uses closed loop automation for operations abstraction and end-to-end (E2E) process visibility. It automates E2E processes across OSS, fulfilment, assurance, and billing, and manages parallel processes. Auto-discovery and mapping of inputs / events from the notification / communication management as well as task and error management modules improve process visibility. Infosys Live operations ingestion adaptors for process visibility facilitate semi-structured and unstructured data management. Moreover, pre-integration with the Hadoop distribution-based ecosystem supports analytics using standard toolsets.
Advanced automation streamlines operations and enables seamless execution across fulfilment, assurance, billing, and corporate processes. The near zero-touch experience across processes enriches employee and customer engagement.
The platform adopts nomenclature-based data persistence to simplify analytics and present aggregated data insights. Self-learning AI / ML models and predictive insights-driven process optimization support omnichannel service, while customizing the experience for business, IT and field operations teams as well as end consumers.