In today's complex business landscape, maintaining high standards of operational efficiency and reliability in both business and technology environments is critical. Managing distributed systems across on-premises, cloud, and hybrid environments while ensuring seamless business operations, such as payment repairs and FX reconciliation, requires robust, real-time observability. This paper introduces a comprehensive observability framework that integrates probabilistic models, machine learning (ML) algorithms, large language models (LLMs), and rule-based systems. This framework dynamically guides event data, structured and unstructured, through intelligent paths to ensure accurate categorization and timely issue resolution, ultimately enhancing key business and technology KPIs.