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.
Discover how Agentic AI is driving practical, strategic advantages for digital and data marketers. From autonomous campaign optimization to personalized customer experiences, this technology empowers your team to focus on high-impact innovation.
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.
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.
In July 2024, Robin was promoted to CTO of Artefact France for his deep technology expertise and management skills. He now leads a large team of data scientists, software engineers and frontend developers, ensuring that his team is at the forefront of technology, with training and curiosity at the heart of his approach.
AI está evoluindo rapidamente para um futuro em que os usuários não pensem mais em modelos, modos ou ferramentas. Em vez disso, os sistemas estão se tornando dinamicamente adaptáveis, ajustando automaticamente a profundidade do raciocínio, selecionando as ferramentas certas e gerenciando recursos em tempo real com base na complexidade da tarefa.
As AI agents increasingly handle tasks like email drafting or resolving customer service issues, one challenge becomes clear: how can these agents communicate effectively - not only with humans but also with the software systems they depend on?
O surgimento de agentes AI nas empresas ocorre em dois níveis: aumento da produtividade individual por meio de agentes de tarefas e redefinição de fluxos de trabalho coletivos por meio de agentes de fluxo de trabalho. Embora essas inovações prometam ganhos de eficiência, elas também apresentam desafios estruturais. Sem uma estratégia bem orquestrada, as organizações correm o risco de uma proliferação descontrolada de agentes e dependências operacionais críticas.
À medida que os agentes AI assumem cada vez mais tarefas como redigir e-mails ou resolver problemas de atendimento ao cliente, enfrentamos um desafio fundamental: como esses agentes se comunicam de forma eficaz, não apenas com humanos, mas com os ecossistemas de software dos quais dependem?
