Artefact Value By Data

IT/OT Convergence: The path to industrial excellence

Imagine a scenario where every operational data point of an industry is continuously captured, organized, scalable, and free from cyber threats. This is the concept of IT/OT (Information Technology/Operational Technology) convergence, an evolution where the synergy between data and technology optimizes efficiency, security, and innovation in manufacturing, enabling high-quality data and robust security that support reliable and strategic decisions.

Adapted and robust, AI is a partner for the future

The Artefact Research Center's mission is to foster an innovation ecosystem around AI and data by encouraging collaboration between university professors and representatives of international partner companies. The goal: cutting-edge research driven by data and the industrial applications of its partner companies.

Artificial Intelligence: Key enablers for achieving real productivity gains

Vincent Luciani, co-founder and Executive Chairman of Artefact, emphasizes that artificial intelligence (AI) must be concretely integrated into a company's collective processes, if it is to deliver real productivity gains. The entrepreneur will be taking part in the MKIA, an event organized by Maddyness and dedicated to AI, at the Salle Gaveau in Paris, on Tuesday April 29.

Measurement, the key to a successful AI strategy

No strategy is effective without measurement! Choosing projects, evaluating the performance of AI agents or the hallucinations of the machine: detailed explanations of the governance you need to put in place to stand out from the crowd thanks to artificial intelligence.

The Future of AI Is Seamless, Adaptive, and Invisible.

AI is rapidly evolving toward a future where users no longer think about models, modes, or tools. Instead, systems are becoming dynamically adaptive—automatically adjusting reasoning depth, selecting the right tools, and managing resources in real time based on task complexity.

Redefining Enterprise Organization for the Agentic Wave.

The rise of AI agents in enterprises unfolds at two levels: enhancing individual productivity through Task Agents and redefining collective workflows via Workflow Agents. While these innovations promise efficiency gains, they also introduce structural challenges. Without a well-orchestrated strategy, organizations risk an uncontrolled proliferation of agents and critical operational dependencies.

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