Meet the Team

Craig Hartzel is the founder and CEO of Hartz AI. He trains SME teams to adopt AI tools they can use independently. He has trained over 500 employees across professional services, charities, sport governing bodies and real estate.

Craig built Hartz AI to give UK businesses a clear, practical path to AI capability. He works directly with SME teams, senior leaders and public sector organisations who want to use AI without the hype.

His approach is hands-on. He runs AI training programmes that leave teams confident enough to use AI tools the same week. He audits operations to find where AI saves real time. He works with leadership teams on long-term AI strategy.

Craig focuses on tools teams can run with independently. He does not sell ongoing dependency. His goal is to build capability, not create reliance on consultants.

Rivka Abecasis leads AI compliance at Hartz AI. She helps clients use AI safely, legally and with confidence. She specialises in UK GDPR, data protection, risk controls and the practical steps organisations need as AI regulation tightens.

Her background spans compliance leadership, policy development and operational governance. She has worked with complex regulatory frameworks and knows how to turn rules into clear actions teams can follow.

At Hartz AI, Rivka builds compliance frameworks, reviews client workflows and advises on safe AI adoption as part of our AI governance services. She focuses on simple guidance, clear safeguards and reducing risk without slowing progress.

Clients trust her because she explains compliance in plain English and gives direct, workable advice. She makes AI safe to use, easy to govern and ready for future regulation.

Samuel Kelly specialises in machine learning patterns for AI models at Hartz AI. He designs and implements ML pipelines, fine-tunes models and builds the data architectures that power intelligent business applications.

His work focuses on selecting the right model architectures, training strategies and evaluation frameworks for each use case. He applies techniques like retrieval-augmented generation, embeddings, classification and sequence modelling to solve real business problems.

Samuel builds production ML systems that are reliable, measurable and maintainable as part of our AI consultancy services. Every model he deploys is tested against real-world data and designed to improve over time as the client's needs evolve.