Understand
Define the application, model, data boundaries, and success criteria.
Define the outcome.
Build with purpose.
A useful AI engagement starts with clear requirements, agreed responsibilities, and a way to measure results.
Evaluate
Assess the workload, compute needs, deployment design, and support scope.
Deploy
Validate the environment and model against agreed acceptance criteria.
Operate
Agree monitoring, maintenance, ownership, and change procedures.
THE FIRST CONVERSATIONStart with
Start with
what you know.
- The application and the people who will use it.
- Expected usage, candidate models, and compute requirements.
- Data boundaries, model licensing, and security requirements.
- Your timeline, success criteria, and operating responsibilities.
COMMON QUESTIONS
A clear starting point.
Do I need to choose a model first?
No. Start with the task and success criteria. Model selection and runtime evaluation can be part of a scoped engagement.
Can we run our own workloads?
Dedicated compute is a proposed engagement option. We confirm allocation, access, isolation, configuration, support, and availability before contracting.
Is the B300 infrastructure available now?
The Toronto deployment is planned. Contact us to discuss requirements and upcoming capacity; a deployment date is not guaranteed on this website.
Will our data stay in Canada?
The AI compute location is planned for Toronto. We assess all relevant storage, access, support, and service providers before agreeing data residency requirements in writing.
START A CONVERSATIONLet’s build around
Discuss your AI project