Solving resource allocation in oncology

Scheduling, outcome prediction and automated treatment planning.

What Gray can do for you

To ensure patient safety and staff happiness, your staff schedules are required to take a large number of constraints into account. From competency requirements on treatment units to contractual restrictions on shifts worked and staff preferences, Gray ensures that departments are running smoothly and at maximal efficiency.


Automated staff scheduling

Automatically generate schedules that mix senior and junior staff for each technology to ensure proper quality and knowledge transfer while optimizing efficiency.


Machine scheduling

Ensure each machine’s productive capacity is being realized by optimizing their usage and staffing.


Schedule validation

Guarantee that your schedules follow all contractual restrictions and visualize shift equity across your team.


On-the-fly requests

Allow your staff to easily request time off or notify the administrator they can’t make it to work. Our portal will display your options so you can quickly approve and act on incoming requests.

The team

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André DiamantFounder & CEO

PhD Medical Physics, specialized in deep learning for outcome prediction in oncology.

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Marc-André RenaudFounder & CSO

PhD Medical Physics, specialized in optimization and radiation therapy treatment planning.

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Stavros KorokithakisFounder & CTO

MSc machine learning, specialized in secure back-end development and deployment.

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Jan SeuntjensFounding Advisor

James McGill Professor. Director of the McGill University Medical Physics Unit

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Louis-Martin RousseauFounding Advisor

Full Professor, Polytechnique Montreal. Canada research chair in Healthcare Logistics.

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Nadia LahrichiFounding Advisor

Associate Professor, Polytechnique Montreal. Canada research chair in Healthcare Logistics.