AI workloads run across multiple clouds and on-premise clusters, each with its own console — which means spend, utilisation and risk stay invisible until the invoice lands. CloudIQ normalises GPU telemetry from every provider into one real-time view of utilisation, cost and health, and runs inside your own environment rather than ours.
A medallion architecture — Bronze, Silver, Gold — that takes GPU telemetry in each provider's own format and turns it into one consistent model, so a figure from one cloud means the same thing as a figure from another.
Live visibility of what every GPU is actually doing across AWS, Azure, GCP, Oracle Cloud and on-premise — so idle capacity surfaces while it can still be reclaimed rather than at month end.
Spend expressed in one comparable unit across providers, which is the only way to answer whether a workload is in the right place. Running on-premise has delivered 50% lower cost-per-TB than hyperscale providers.
From a total that looks wrong to the individual instance responsible, without exporting to a spreadsheet or asking four different consoles the same question.
Alerts into Slack and Teams that carry enough context to act on — closed-loop, so an alert tracks through to what was done about it rather than being acknowledged and forgotten.
CloudIQ runs inside the customer's own VPC. Telemetry about your infrastructure never leaves your environment, which matters when the infrastructure itself is sensitive.
GPU telemetry from five providers is just another multi-source integration: different formats, different meanings, no shared key. We built it the way we build any data platform.
Deployable inside your own VPC rather than as a service we host. UK-built, and the data stays where it started.
Numbers that cannot be compared across providers do not answer the only question that matters, which is whether a workload is running in the right place.
CloudIQ is one of several solutions we've built in-house. If you have an infrastructure or data problem that looks like this one, we'd be glad to talk about it.