The telecommunications industry is at a critical turning point. While traditional automation strategies have delivered incremental operational gains through process centric workflows, they fall short of enabling true autonomy, adaptability, and business agility in an increasingly dynamic and data intensive ecosystem. 3rd Phase of our Catalyst project; aims to accelerate the transition from process-driven automation to value-driven autonomous network operations (ANO) by introducing a federated, agent-based architecture grounded in TM Forum’s Open Digital Architecture (ODA) and Autonomous Operations Maturity Model (AOMM). What We Are Doing We are designing and validating a cognitive, Gen AI-enabled service management layer for Communication Service Providers (CSPs). At its core, the project introduces: * Agentic AI Mesh: A network of interoperable AI agents that coordinate decisions across network, IT operations, customer experience, and business domains. * Temporal Knowledge Graph (TKG): A dynamic, context-aware memory model that enables agents to reason over time, correlate events, and surface historical insights. * Natural Language Interface: Operators interact with the system via natural language queries, receiving contextualized, policy-driven responses aligned with intent and business outcomes. Why We Are Doing It Current OSS-based automation approaches remain predominantly task-focused and siloed, limiting their impact on customer experience, monetization, and resilience. According to TM Forum's AOMM survey: * Over 76% of CSPs prioritize fault prevention and ticket resolution. * Yet 49% report having no strategic roadmap for ANO. * 69.57% face data availability and quality issues, while legacy system complexity continues to inhibit transformation. To address these gaps, the project redefines OSS transformation around value streams, such as: * Resilience Streams * QoS/Experience Streams * Monetization Streams * Sustainability Streams These streams are enabled and managed by an underlying network of AI agents, making autonomous operations responsive to real-time business and service objectives. How We Are Doing It The architecture is built upon four foundational principles: 1. Federated Agent Framework Agents for site design, change management, resolution dispatch, network slicing, and experience assurance are integrated into an interoperable AI mesh, delivering closed-loop automation and policy-aware collaboration. 2. Temporal Knowledge Graph Integration The TKG allows systems to maintain, recall, and reason across time-based network and service performance data, providing explainability and historical correlation to enrich agent actions. 3. Intent-to-Execution Translation By linking natural language interfaces to value stream models, the system enables intuitive operator input that drives automated orchestration across service domains. 4. AI Governance & Data Control A governance layer ensures traceability, security, and auditability, supporting policy compliance and human oversight across all autonomous functions. Benefits Operational Benefits * Faster detection and prioritization through proactive, AI-driven fault correlation * Reduced Mean Time to Resolution (MTTR) via closed-loop service assurance * Increased automation coverage across ITSM, network, and customer operations Business Impact * 15% revenue uplift in marketplace models via B2B2X orchestration (Middle East CSP use case) * >25% energy savings by optimizing resource allocation and reducing unnecessary site visits * Enhanced SLA compliance and NPS improvement through predictive experience streams Strategic Value * Accelerates CSP progression on TM Forum’s Autonomous Operations Maturity Model * Lays the foundation for new business models based on service intent, contextual policy, and dynamic value streams * Enables telecom-native, cloud-delivered intelligence through partnerships This Catalyst delivers a foundational shift from process-centric automation to value stream-driven autonomous network operations (ANO). It enables Communication Service Providers (CSPs) to operationalize agentic AI models orchestrated by a Temporal Knowledge Graph (TKG), creating dynamic, policy-aware, and business-aligned decision ecosystems.