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Trust framework with Risk Analysis and Conflict Resolution for agentic autonomous networks (TRACR)

URN C26.0.926
Topics AI (Artificial Intelligence), Autonomous networks, Privacy & trust

Attain a fully autonomous network with an agentic AI platform built on a trust framework, reinforcement learning, conflict resolution, and traceability

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Trust Framework with Risk Analysis & Conflict Resolution (Trusted Autonomy Platform) The project tackles one of the most pressing challenges facing CSPs today: how to safely accelerate network automation while reducing operational complexity and business risk. As telecom environments evolve to support AI-driven, closed-loop, and autonomous operations, the need for transparent, explainable, and trustworthy decision-making becomes critical. This Catalyst introduces a Trusted Autonomy Platform—an agentic, AI-enabled framework that embeds risk analysis, conflict detection, and automated resolution into the heart of network operations. The platform enhances operational efficiency by ensuring that every autonomous action can be traced, justified, and trusted. It supports CSPs on their journey toward Level 4+ Autonomous Networks, delivering measurable improvements in reliability, service assurance, and cost efficiency. By enabling CSPs to confidently adopt advanced automation while maintaining governance and oversight, this project helps operators modernize safely, respond faster to change, and ultimately deliver better customer experiences.

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Champion
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