Скачать или смотреть Multi Agent AI and Network Knowledge Graphs for Change — Ola Mabadeje, Cisco

Traditional ticketing and testing workflows for change management and network operations often operate independently and lack critical real-world context and adaptive decision making capabilities. This fragmented approach results in delayed resolutions, repeated incidents, escalations, and dissatisfied stakeholders.

This session explores an innovative solution leveraging the synergy of natural language processing from IT Service Management (ITSM) systems, Multi-agent reasoning, and dynamic context derived from live knowledge network graphs. Attendees will gain insights into an end-to-end architecture where natural language intents from ITSM tickets seamlessly integrate with experts AI agents for complex workflow tasks, supported by continuous network knowledge graph ingestion pipelines.

Through a detailed production case study, we will demonstrate how Agentic reasoning combined with dynamic network knowledge graph contexts significantly improves critical validation and workflow interactions. The showcased results will highlight dramatic improvements in ticket resolution efficiency, accuracy of network testing, and overall execution quality, delivering tangible value to both technical teams and business stakeholders.