Predictable Spend, Maximum Value
FinOps
Cloud unlocks speed and scale, but without disciplined financial operations it also unlocks runaway bills. Our FinOps practice combines Microsoft tooling, engineering rigour, and cultural change so finance, engineering, and product teams share a single, accurate view of cloud spend — and the levers to optimise it.
FinOps delivered with native Microsoft tooling
Infrastructure (Azure) 
Microsoft Cloud Partner 
Digital App Innovation (Azure) Key Capabilities
Cost Visibility & Tagging
Establish a tagging taxonomy, chargeback model, and cost allocation framework so every pound of Azure spend can be attributed to a team, product, or workload.
Rightsizing & Waste Elimination
Identify under-utilised VMs, idle databases, orphaned disks, and over-provisioned services, then rightsize or decommission with engineering-led recommendations.
Reservations & Savings Plans
Model commitment-based discounts across compute, databases, and storage to lock in 30–60% savings on predictable workloads without losing flexibility.
Budgets, Alerts & Anomaly Detection
Configure Azure Cost Management budgets, anomaly alerts, and forecasting so cost surprises are caught early and accountability sits with the right teams.
AI & GPU Cost Control
Bring token, GPU, and Azure OpenAI capacity spend under control with quotas, model routing, prompt optimisation, and continuous monitoring of inference costs.
FinOps Operating Model
Embed FinOps practices, KPIs, and rituals across finance, engineering, and product so optimisation becomes continuous rather than a one-off exercise.
Typical Azure cost reduction in first six months
AI workload cost reduction with model routing
Spend tagged and attributable to teams
Anomaly detection on cost spikes
Where FinOps drives value
Cost optimisation review
A focused engagement to surface immediate savings across compute, storage, networking, databases, and licensing — with prioritised, costed recommendations.
Tagging and chargeback rollout
Define and enforce a tagging policy across subscriptions, then build chargeback or showback reporting so business units own their consumption.
Reservations and savings plan strategy
Analyse usage patterns and build a portfolio of reservations, savings plans, and spot capacity that balances commitment risk against discount.
AI and Azure OpenAI cost governance
Implement quotas, model routing, capacity reservations, and token budgeting so generative AI workloads stay predictable as adoption scales.
FinOps platform and reporting
Stand up Cost Management dashboards, Power BI reporting, and integrations with finance systems so executives and engineers see the same numbers.
Ongoing optimisation as a service
Continuous FinOps run by Synapx engineers — monthly reviews, action backlogs, and measurable savings tracked against agreed KPIs.
A proven delivery approach
- 01 Step
Assess
Baseline current spend, tagging coverage, commitment portfolio, and FinOps maturity to identify quick wins and structural opportunities.
- 02 Step
Design
Define the target operating model, tagging taxonomy, reporting, and policies — aligned to FinOps Foundation principles and your business structure.
- 03 Step
Implement
Roll out tagging, budgets, reservations, rightsizing, and anomaly detection in controlled waves, embedding controls in DevOps pipelines.
- 04 Step
Operate
Run continuous optimisation cycles — measuring, reporting, and acting on savings — optionally under Synapx-as-a-Service.
Frequently asked questions
What savings can we realistically expect?
Clients moving from un-optimised Azure estates typically see a 20–40% reduction in the first six months, with a further 5–15% from ongoing optimisation. AI and generative workloads often deliver 30–50% savings through model routing, quotas, and prompt optimisation.
Do we need to be on Azure already to benefit?
No. We embed FinOps practices into migrations, landing zones, and platform builds from day one so spend is governed before it grows. Engaging early avoids expensive remediation later.
How do you balance savings with engineering velocity?
FinOps is about value, not just cost. We focus on eliminating waste and right-sizing without restricting teams, using policy-as-code and automated guardrails so engineers retain autonomy within agreed budgets.
Can FinOps cover AI workloads specifically?
Yes. We govern Azure OpenAI, Azure AI Foundry, GPU compute, and third-party model spend with quotas, capacity reservations, model routing, token budgeting, and continuous monitoring tailored to AI consumption patterns.
Do you align to the FinOps Foundation framework?
Yes. Our practice is built around the FinOps Foundation principles, capabilities, and personas, combined with Microsoft Cost Management, Azure Advisor, and Azure Carbon Optimisation tooling.
Can Synapx run FinOps for us as a managed service?
Yes. Synapx-as-a-Service delivers ongoing FinOps — tagging hygiene, optimisation backlog, reservation management, anomaly response, and monthly executive reporting — with savings tracked against agreed KPIs.
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