
Logiciel helps enterprises design, build and operate cloud cost governance and FinOps engineering practices across AWS, Azure, data platforms, SaaS environments and AI workloads. From FinOps governance and AWS cloud cost management to Azure cost governance, cost allocation, optimization workflows and AWS AI and ML services visibility, we help teams control cloud spend without slowing product delivery.
We build FinOps engineering practices that make cloud cost visible, accountable and easier to optimize.
to business and platform priorities
for ownership, budgeting, forecasting and cost reviews
for accounts, services, tags, budgets and usage trends
aligned with multi-cloud reporting and operational controls
for AWS cloud machine learning, AWS in machine learning workloads and data platforms
for compute, storage, databases, AI services, environments and observability tools
Current-state assessment, FinOps maturity review, cost ownership model, reporting design and phased implementation roadmap.
Operating model design for budgets, chargeback, showback, tagging, cost allocation, forecasting, policy controls and cost review cadences.
AWS cost dashboards, account-level reporting, service usage visibility, tagging policies, anomaly detection and optimization workflows.
Azure cost visibility, budget controls, resource tagging, workload reporting, cost allocation and governance workflows.
Cost tracking for aws and machine learning workloads, AWS cloud machine learning usage, AWS machine learning server patterns and ML AWS environments.
Governance for machine learning services AWS, AWS AI and ML services, Amazon cloud machine learning and AWS Amazon machine learning workloads.
Ongoing cost monitoring, reporting, optimization reviews, anomaly analysis, governance updates and continuous improvement.
A standing team of cloud engineers, FinOps consultants, data platform specialists and DevOps experts embedded into your cloud cost governance roadmap.
Senior FinOps governance specialists, AWS cost engineers and cloud platform consultants who strengthen your internal finance, platform or engineering teams.
Fixed-scope engagements with defined cost visibility outcomes, governance milestones, optimization targets and success baselines agreed up front.
Patterns from our cloud, DevOps and data engineering teams that help enterprises manage cloud spend as an engineering discipline, not just a finance report.
How we structure ownership, tagging, budgets, forecasting, optimization backlog, engineering accountability and executive reporting across teams.
A practical approach to ranking cost priorities by spend growth, business value, workload criticality, optimization potential and operational risk.
We assess AWS, Azure, AI workloads, data platforms, account structures, tagging quality, cost reports and governance maturity.
We identify cost owners, products, teams, services, machine learning workloads, environments and the largest cloud cost drivers.
We build dashboards, tagging standards, budget controls, forecast workflows, anomaly alerts, reporting views and approval processes.
We implement cost controls for compute, storage, databases, AI services, environments, observability and data movement workflows.
We hand over a repeatable cloud cost governance practice, including ownership, KPIs, review cadences, runbooks and improvement workflows.



Teams that needed to ship fast, and did. Here's what partnering with Logiciel felt like from the inside.
Cloud Cost Governance FinOps Engineering includes cloud cost governance strategy, FinOps governance, AWS cloud cost management, Azure cost governance, tagging, budgets, cost allocation, forecasting, optimization workflows, AI cost visibility and managed operations.
Enterprises need cloud cost governance because cloud spend grows across teams, products and services. Governance helps assign ownership, improve visibility, prevent waste and connect cloud investment to business value.
FinOps governance creates shared accountability between finance, engineering, product and leadership teams. It uses budgets, tagging, cost allocation, forecasting, cost reviews and optimization workflows to manage cloud spend continuously.
Yes. Logiciel supports cost visibility for AWS and machine learning workloads, including model training, inference, experimentation, data movement, AWS AI and ML services and AWS cloud machine learning usage.
Yes. We support Azure cost governance through budget controls, tagging policies, resource reporting, subscription visibility, cost allocation, anomaly review and optimization workflows.
Common deliverables include cost dashboards, tagging standards, budget workflows, showback reports, chargeback models, anomaly alerts, optimization backlogs, governance policies, runbooks and executive reporting.
You retain ownership of all dashboards, cost reports, tagging policies, budget workflows, optimization recommendations, documentation, runbooks and implementation assets.
Yes. We run managed FinOps operations with reporting, anomaly detection, cost reviews, optimization backlog management, governance updates and continuous improvement.
Ready to turn Cloud Cost Governance (FinOps) Engineering into a reliable foundation for cost-aware cloud delivery? Partner with Logiciel to improve AWS cloud cost management, strengthen FinOps governance and control AI, data and infrastructure spend with confidence.