Team of Business and AI

Dr. Nabil Belgasmi is an AI expert with over two decades of experience across academia and industry, specializing in Computer Science with a focus on evolutionary multi-objective optimization. He is the CEO and founder of BUSINESS & AI (founded in 2020), an AI company delivering products and services for regulated and data-intensive industries across Europe, the Middle East, and Africa, where he leads AI-driven decision-intelligence initiatives combining predictive and prescriptive analytics, optimization, and scalable monitoring. He has delivered AI programs for global enterprises and regulated institutions, including Fortune 500 organizations such as Volkswagen SA, as well as financial institutions and leading telecommunications companies, with a focus on explainable, production-grade AI for financial crime compliance, treasury transformation, and regulatory risk management—covering self-explaining AML systems beyond rule-based approaches, intelligent transaction scoring, continuous monitoring, and automated cash forecasting. A core pillar of his RegTech work is RegVision, BUSINESS & AI’s regulatory risk analysis and mapping solution, powered by specialized LLMs and agentic reasoning, combining multi-agent workflows, task-tuned SLM components, and graph-based reasoning to convert regulatory texts into auditable, scalable risk mapping that goes beyond static matrices toward continuously updated, evidence-driven models. He introduced a multi-objective deep reinforcement learning approach for cash planning and optimization, recognized with the Best Applied AI Project Award at an AI conference in Dubai (2018), and he develops LLM-enabled knowledge-graph approaches for adverse media analysis, regulatory screening, and next-generation AI-driven compliance strategies. Dr. Belgasmi publishes in leading AI and operations research venues, including ECAI, IJCAI, WSC and OR journals, and serves as an Industrial Board Member of Engineering Applications of Artificial Intelligence (EAAI), helping bridge applied research and enterprise-scale AI adoption.

Maram BAKINI. Data Scientist with experience in Generative AI and Natural Language Processing, working on Retrieval-Augmented Generation (RAG) systems and fine-tuning Small Language Models (SLMs) using LoRA for entity extraction and domain-specific applications, as well as fine-tuning custom NER models. She has designed intelligent search systems and real-time monitoring dashboards. Her projects include AI-powered chatbots for HR automation and AI-based customer service evaluation. Currently pursuing an MS in Intelligent Systems and IoT, she holds a BS in Computer Science. Her expertise focuses on building domain-specific AI solutions for real-world applications.

Omar OUELHAZI. A full stack data scientist. He holds a master's degree in data science for Business, with a focus on research and development. His expertise spans machine learning, NLP, data engineering, and Generative AI, with hands-on experience designing and deploying agentic AI systems and GenAI workflows. He has built Graph-RAG pipelines for enterprise GenAI workflows, developed multi-agent architectures for complex automation use cases, and worked on deep-learning models for financial market prediction and automated cryptocurrency pattern-detection platforms. His work sits at the intersection of experimentation and practical implementation — from orchestrating AI agents to shipping production-ready GenAI systems.

Fadi KHARROUBI. Computer Science Engineer specialized in Artificial Intelligence and Data Science, with hands-on experience in designing and deploying end-to-end machine learning systems. Currently working at Business&AI, developing intelligent solutions that support strategic decision-making and optimize operational workflows. Previously built an AI-driven real-time application usage analysis system, developing custom image classification models (CNNs, transfer learning) and managing large-scale datasets across train/validation/test pipelines. Experienced in model optimization, data preprocessing, CRISP-DM methodology, and deploying solutions in cloud environments. Passionate about transforming complex data into scalable AI systems that generate measurable business impact.