Most enterprises can report what AI cost them. Far fewer can say which team owns it, whether it was approved, or what it returned.
FinOpsly closes that gap. The platform governs AI spend on the same cost model that carries the cloud, data platform and SaaS an AI workload consumes, so a business unit sees the full cost of an AI initiative instead of four disconnected bills.
Capabilities include:
Cost estimation before deployment. Model an architecture and get a priced workload across model APIs, GPU capacity, warehouse consumption and storage, with the assumptions on screen. Weigh model choices against consumption you have actually measured.
Attribution that holds up in a chargeback cycle. Spend resolves to owners, teams, applications, business units and customers through hierarchies nine or more levels deep. Tagging is standardized across providers, keys and resources are labeled in bulk from plain-language rules, and whatever remains unattributed is published as a number, not absorbed.
Guardrails that act. Set budgets by project, team or API key. Catch anomalies with root cause and route them to whoever owns the resource. Surface waste that provider tooling misses, using FinOpsly's own detection models. Plan commitments across AWS, Azure and Google Cloud. Park idle compute on approved schedules, reversibly.
Financial results you can defend. Automated chargeback in a single cycle. Savings measured as what reached run-rate against a no-action baseline. Unit economics down to cost per call, per active user and per customer served.
For technology and finance leaders accountable for what AI spend returns.
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CloudZero helps businesses optimize cloud spend with full visibility into costs—so they can reduce wasteful spending and improve their unit economics. Unlike other solutions, we take an engineering-led approach to cost optimization, helping teams understand what drives 100% of their operational cloud spend, empowering them to reduce risk, minimize waste, and maximize profit.
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Zesty
Zesty’s cloud infrastructure optimization platform offers solutions for databases, storage and compute. It also helps companies reduce cloud spending. Zesty, powered by machine learning and automation, provides FinOps/DevOps teams actionable insights to fit real-time applications and achieve optimal utilization of cloud resources.
Zesty Commitment Manager optimizes EC2 discount plans and RDS automatically, ensuring maximum coverage with deeper savings. This is done with minimal financial risk.
Zesty Disk automatically scales EBS volumes up or down to match real-time applications needs. This optimizes storage utilization, eliminates the risk of downtime and reduces costs by up 70%.
Zesty Insights gives you a clear view of your potential savings, unused resources and offers actionable suggestions that will help you focus on saving the most money.
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Eco
Automated Optimization for AWS Savings Plans and Reserved Instances streamlines the entire process of planning, purchasing, and enhancing your cloud commitments portfolio. Eco facilitates the lifecycle management of reserved instances, crafting a cloud commitment portfolio that is both high in return on investment and low in risk, tailored to your current and future requirements. By pinpointing and liquidating unused capacity while acquiring suitable short-term, third-party reservations from the AWS Marketplace, Eco allows you to reap the benefits of long-term pricing without being tied down financially. This approach ensures that you achieve the highest possible return on investment from your cloud commitment purchases through thorough analysis, adjustments, and alignment of unutilized reserved instances and Savings Plans with resource demands. Additionally, Eco automates purchasing strategies for reserved instances throughout their lifecycle in the AWS Marketplace, guaranteeing that workloads are perpetually operating at the best pricing. Collaboration between Finance and DevOps teams is enhanced by providing full transparency into compute consumption and automating the selection of optimal reserved instances, ultimately leading to a more efficient cloud resource management process. With these capabilities, organizations can adapt more swiftly to changing needs while optimizing their cloud expenditure.
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