Leaders

Gamal Mubarak

Gamal is an AI and robotics engineer who applied AI agents to go-to-market workflows and saw how quickly capabilities are moving. Models are now getting close to sustained, multi-step execution, but the missing piece is the training harness: the environment that forces real competence, long-horizon reliability, and learning under real constraints.

That pushed him back to the reinforcement learning foundations he learned in robotics. At Celeri, Gamal leads sales and go-to-market, working directly with customers in financial services to understand their workflows and build solutions that actually work in production.

Carla Griffiths

Carla has a PhD in Neuroscience from UCL, where she worked in John O'Keefe's Nobel Prize-winning lab researching how neural systems generalise from sparse feedback. Her main goal is to figure out why generalisation occurs so naturally in the human brain, but machines struggle.

After switching to industry machine learning, the connection became obvious: white-collar work is the perfect reinforcement learning environment. Workers have clear reward signals (expert corrections), rich state spaces (complex documents and decisions), and massive economic value.

At Celeri, Carla focuses on the back-end algorithms behind the product, building systems that learn from real human work in the field rather than synthetic training data.