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Description
At AI Week 2026, we will present an architecture for autonomous, adaptable agentic systems oriented toward continuous learning.
At the core of the solution, reasoning is separated from execution: a first multi-agent system composed of “Actors” and “Critics” collaborates in an adversarial setup to define the action strategy, also leveraging the history of past executions. A second multi-agent system, organized hierarchically, is responsible for execution and real-world implementation through specialized agents and operational functions, known as “Tools”.
The system implements a reinforcement learning paradigm, where evaluating agents compare the generated outcome with user expectations, feeding a global and personalized memory that ensures continuous performance improvement and prevents the repetition of errors.
The infrastructure, which is portable on-premise, guarantees full data sovereignty and security, featuring a modular and LLM-agnostic design that eliminates vendor lock-in risk. Finally, the multi-agent architecture ensures maximum explainability and transparency of decision-making processes, enabling the solution to evolve and scale in close collaboration with end users through co-design.
TIM Enterprise is TIM’s business unit delivering integrated digital solutions to enterprises and public sector organizations, focusing on innovation, sustainability, and security to drive digital...
