CellMinder is designed to provide complete, end-to-end traceability of materials, processes, and data. This enables reproducible cell culture and assay development, with robust audit trails across time, teams, and sites.
Experiments are defined using reusable protocols expressed in biological terms, not programming abstractions. A built-in multi-factorial design engine handles the complexity of experimental planning, making sophisticated investigations easier to run and scale.
AI-guided perception enables explicit verification of position and state, allowing the system to act with precision rather than assumption. Each step is visually confirmed, and activities are planned to tolerate variation and deliver reliable results.
Stephen is a chartered engineer with a PhD in medical robotics and over 20 years’ experience delivering robotic, automation, and software systems from concept to production. He has led teams across laboratory automation, medical devices, and autonomous robotics, with a focus on building reliable, scalable systems for real-world use.
Jocelyn is a software engineer with a PhD in Chemistry and over 15 years’ experience designing and delivering reliable, data-intensive systems. Her background spans laboratory automation, cloud infrastructure, IoT, and large-scale automated testing, with a strong focus on traceability and validation, and production-ready engineering.
M is an experienced early-stage investor with a strong interest in forming and supporting founding teams. He contributes a systems-driven, operational mindset shaped by work in safety-critical environments, alongside practical experience helping early companies grow responsibly.
