We make AI technologies understandable for companies of all sizes. Our mission is to bridge the gap between complex AI systems and business understanding.
As AI systems become more complex, understanding their decisions grows increasingly challenging. Companies struggle to interpret and trust outputs from their AI models, creating barriers to effective implementation.
CloudExplain bridges this gap with tools and expertise that make AI reasoning transparent. We help businesses decode complex model behaviors, enabling confident decision-making and trustworthy AI integration.
Our founders bring together 25+ years of combined experience in AI, data science, and enterprise solutions.
8+ years in Sales/Strategy/AI across Financial Services (Allianz) and Big Tech (AWS, Microsoft), initiated and managed advanced analytics, GenAI, digital transformation, and automation projects.
8+ years as Data Scientist in Automotive, Energy, and Telco, Explainable AI (XAI) Engineer, key maintainer of the SHAP framework (+23k GitHub stars) contributing 50% of SHAP in the past 6 months.
10+ years as Data Scientist in Retail and Telco, developed Explainable AI models for 10M+ customers, and designed/implemented data products and dashboards.
Our extended team includes industry advisors and specialists who bring additional expertise to our mission.
10+ years in Delivery, Consulting, Marketing, and Strategy. Caroline brings deep industry knowledge and strategic insights to help CloudExplain navigate complex enterprise requirements and market dynamics.
Connect with our team to learn how CloudExplain can make your AI systems transparent and trustworthy.