Demand map
List public workloads, sensitivity level, volume, latency, and audit needs.
The demo proves demand. Government teams can use AI today. The gap is not imagination. The gap is a practical Canadian route for sensitive work.
Start with demand, not concrete. A data centre becomes financeable when enough credible workloads are attached to it.
List public workloads, sensitivity level, volume, latency, and audit needs.
Shortlist sites with grid capacity, fibre, cooling, zoning, and resilience.
Blend tenant commitments, public guarantees, and infrastructure capital.
Commission secure operations, audit logs, routing controls, and model access.
Run the first government AI workloads with published cost and evidence metrics.
The public sector does not need to build everything. It needs to create a credible demand signal that builders and capital can underwrite.
Illustrative structure for a first Canadian public-sector AI compute lane.
The hard parts are operational. The meeting has to surface these early.
Useful for a CAO, CIO, deputy minister, builder, utility, privacy lead, and procurement lead.
Pick three workflows with real volume: grants, procurement, permits, records, or service triage.
Classify public, sensitive, protected, regulated, and confidential workloads.
Name the anchor tenants, budget owners, and minimum spend that makes financing real.
Power, interconnect, cooling, security certification, procurement, GPUs, and model availability.
One Canadian route. One sensitive government workflow. Published cost, latency, quality, routing, and audit metrics. If it works, expand it.