Know where your AI energy is going.
Matcha connects GPU power telemetry with AI workload traces to show which models, training runs, inference requests, tenants, and workflows are driving energy use.
Connects with your AI infrastructure stack.
Matcha plugs into the telemetry, workload, and cluster tools your team already uses — no migration required.
1
Connect GPU telemetry
2
Link workload context
3
Sync with your observability layer
Built for AI infrastructure teams.
Whether you operate GPU clouds, AI labs, or enterprise clusters, Matcha adapts to how your workloads run.
Stop guessing which tenants are driving energy use.
Track which customers, models, and workloads are driving power use across your fleet.
Understand energy across training and inference.
Compare training runs, inference services, and agent workflows by energy, cost, and efficiency.
Telemetry
Input
Report
Output
Bring accountability to shared AI clusters.
See energy and cost by team, tenant, model, and workflow — without relying on tokens or cloud bills alone.
