Financial services
Risk simulations and internal AI assistants may require strong audit trails, defined data boundaries and recovery testing. Establish model oversight and data permissions before capacity decisions.
WORKLOADS / USE CASES
Different work.
Different requirements.
Use these illustrative briefs to identify questions for your architecture team. They are potential applications, not services currently supplied.
Scientific research
Simulation and model training can involve large batch jobs, specialised libraries and high-throughput data paths. Benchmark the full dataset workflow and validate repeatability.
Healthcare technology
Research analytics and administrative assistants raise data-governance and validation questions. Clinical deployment requires separate professional, regulatory and safety review.
Manufacturing
Visual inspection and digital-twin experiments may involve local inference plus central training. Map latency needs, equipment integration and disconnected operation.
Telecommunications
Distributed analytics and network operations can span many locations. Explore tenancy boundaries, observability and central versus local control.
Energy & enterprise software
Engineering analysis, document retrieval and application modernisation can coexist. Identify steady workloads, burst demand, data dependencies and the skills needed to operate them.
Turn requirements into a scenario.
The planner compares capacity, facility energy and selected costs. It does not predict application throughput.
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