Microrbit Tech Conference – Paris
The Microrbit Global Empowerment 2026 conference in Paris is a major event dedicated to women’s empowerment, leadership, and wellness, expecting over 500 attendees, 300 speakers, and 100 startups. Held at the Novotel Paris Roissy CDG Convention, it features sessions on women’s rise, visionary leadership, mental health, gender equity, and wellness advocacy. The conference fosters networking among professionals, investors, and startups, with a focus on innovation, strategic partnerships, and transformative ideas. Dr. Michelle Boese is among the key leaders featured.
Abstract
Human cognition has produced digital technologies whose volume, velocity, and variety now exceed our capacity to interpret them reliably. In the era of big data and generative AI, veracity has become the dominant challenge, as AI-generated content and misinformation accelerate the transition into a post-truth environment. In such a context, individuals and organizations that ground decisions in factual, reality-based knowledge (rather than opinions and biased narratives) gain a decisive advantage.
However, distinguishing true from false is increasingly complex. Addressing this challenge requires robust methodologies managing digital complexity, trace the lineage from facts to decisions. This presentation introduces a methodology based on knowledge graphs combined with dedicated AI pipelines for graph creation and interpretation. Graph metadata form an end-to-end, linked backbone integrating both data and logic (EaaC: Everything as a Code) enabling traceable and explainable KaaS (Knowledge as a Service) enabling optimal decision-making. We will present the methodology, the supporting framework and tech stack, and multiple use cases from the Life Sciences industry, demonstrating how knowledge graphs and graph RAG (Retrieval Automated Generation) enables trustworthy automation, responsible AI adoption, and scalable data-centric digital transformation.
Keywords
Digital transformation, applied AI, knowledge graphs, generative AI governance, automation in healthcare, data infrastructure, responsible AI, LLM operations and evaluation.
