Solutions
Spend, capacity and utilisation in one picture — instead of four portals and a spreadsheet.
Operations intelligence joins billing data to what your infrastructure is actually doing, so the recurring argument about cost has evidence on both sides of it.
Everyone agrees the cloud bill is too high. Nobody can say which part.
Finance sees a monthly total and a growth rate. Operations sees utilisation graphs in a different console. Neither view answers the question leadership actually asks, which is some version of: what would it cost us to stop paying for the capacity we are not using, and what would break.
The blocker is almost never analytical sophistication. It is that billing records and performance telemetry live in separate systems, keyed differently, at different granularities, with no reliable link back to the application or cost centre that owns the workload. Producing one credible number takes a week of manual reconciliation, so it gets produced once a quarter and trusted for about a fortnight.
The same gap defeats the follow-up question. Once you have identified an over-provisioned estate, someone still has to turn that into scheduled, owned, tracked work — and that is where consolidation programmes quietly die.
What we build
From telemetry to a decision somebody actually makes
Unified inventory
On-premise and cloud compute reconciled into one model — clusters, hosts, instances and their storage — deduplicated across the discovery sources that each hold a partial view.
Cost attribution
Billing joined to workloads and mapped to the cost centres and applications management already reports against, so spend is discussed in the same units as the rest of the business.
Right-sizing evidence
Sustained utilisation profiled over meaningful windows rather than instantaneous snapshots, with headroom, seasonality and the peak that actually matters made explicit before anything is recommended.
Capacity and coverage gaps
Backup policy, retention and immutability checked across the estate — including the instances that quietly have no policy attached at all, which is a category that exists in every environment we have looked at.
Conversational analysis
An assistant grounded in the same curated datasets, so an operations lead can ask a question in plain language and receive an answer traceable to the underlying rows rather than a plausible invention.
From insight to ticket
Recommendations become tracked work in the systems your teams already use, with the supporting evidence attached, so the finding survives the handoff into delivery.
What changes
What this changes
The cost conversation gets specific
Discussions move from a total and a percentage to a named list of workloads, their utilisation, their owner and what changing them would save. Specificity is what unlocks the decision.
Right-sizing stops being contentious
When the utilisation evidence is visible to the application owner as well as to operations, resistance drops sharply. Most objections are about the absence of data, not the presence of a plan.
Gaps you did not know you had
Backup, retention and policy coverage analysis reliably finds a meaningful slice of the estate with no protection configured. Discovering this before an incident is worth considerably more than the cost work that surrounds it.
A reusable operating picture
The joining layer built for cost analysis is the same substrate later needed for capacity planning, resilience reporting and workload placement. The second question costs a fraction of the first.
Bring the cost question you cannot currently answer.
If producing a defensible right-sizing recommendation currently takes your team a week of spreadsheet work, that is the problem worth fixing first.