From billing data to a decision
Spend data is scattered, inconsistent and out of context. We fix that in four steps, using the tools you already run.
-
Collect
Billing exports, usage records and metering from every cloud, data platform and AI service you use.
-
Unify
Vendors describe cost in different ways. We map it all to one structure, with the open FOCUS standard as the backbone, so a cloud hour, a data credit and a million tokens can be compared and added up.
-
Add context
Every line item is enriched across every dimension the business cares about: teams, products, environments, contracts, budgets and owners. Nothing stays anonymous.
-
Decide
The same numbers, shaped for each role, so every decision starts from one source.
One set of numbers, three ways to use it
Architects, system managers and product teams
See utilisation, capacity and performance next to cost for every service, workload and release, so design trade-offs have a price before they ship.
Finance
Follow budgets, forecasts and actuals on any dimension and at any level of detail: business unit, product, environment, vendor or contract. Showback and chargeback that reconcile.
Leaders
Make investment, sourcing and AI decisions from one trusted view, and answer the question every board asks: what is technology spend buying us?
Optimisation that sticks
Savings come from two kinds of lever. We pull the commercial ones centrally, the technical ones sit with the teams that run the workloads, and every action is tracked to an owner until the saving shows up in the numbers.
Right costing
Managed centrally, once for everyone
- CommitmentsSavings Plans, reservations and committed-use discounts, sized to steady demand.
- Licensing benefitsAzure Hybrid Benefit and bring your own licence, where you already own the right.
- Dev and test pricingLower rates for non-production work, where the vendor offers them.
- Vendor termsPricing and consumption agreements, negotiated from usage and trend data.
Right sizing
Owned by the teams that run the workloads
- RightsizingMatch size to real utilisation and capacity needs.
- SchedulingSwitch off what nobody uses at night and at weekends.
- ModernisationMove to newer, cheaper generations of the same service.
- Clean-upRemove orphaned disks, snapshots and idle resources.
- PlacementRun each workload in the region that fits both the need and the price.
Data platforms and AI have levers of their own
SnowflakeWarehouse sizing, auto-suspend and query tuning to cut wasted credits.
Microsoft Fabric and SAP DatasphereCapacity sizing and workload scheduling, so you pay for what you use.
AI platformsModel choice, prompt caching, batching and token budgets, set before usage scales.
Find
Spot waste and unused discounts in the unified data.
Prioritise
Rank by value and effort, and give every action an owner.
Act
We pull the central levers. Your teams pull the technical ones.
Prove
Track realised savings against forecast, in the numbers Finance already uses.
Then around again, because workloads and prices keep changing.
Two ways to work with us
Advisory
Fixed-scope work that leaves something running. We set up the foundations and hand them over.
- A cost baseline and a FinOps operating model
- Allocation and tagging rules that hold
- Commitment and licensing strategy
- AI cost governance before spend scales
- Vendor negotiation support
FinOps as a service
We act as your FinOps team, with a named lead and a steady monthly rhythm.
- Monthly reporting, showback and chargeback
- Budget and forecast follow-up
- An optimisation backlog with owners
- Board and leadership packs
- Your data stays in your own systems
We don’t sell a tool and we don’t resell cloud, so our advice carries no commission.
Behind OpFinQ
Led by a FinOps Certified Professional with an Executive MBA and around 70 enterprise engagements behind them.
Some of those engagements had annual cloud spend of up to USD 1bn. Our focus is the part of the stack that is hardest to explain on an invoice: multi-cloud, data platforms and AI.