Start Governing Your AI and Cloud Spend.
Cloud and AI adoption accelerate innovation. But without the right financial controls, they also create escalating costs, waste, and complexity that traditional budgeting wasn’t designed to manage.
AI is quickly becoming the newest — and often least understood — part of the technology bill. Enterprise GenAI spend is already estimated at $37 billion, and 98% of FinOps teams now manage AI cost. Yet most organizations still cannot say which team, model, or workload drove last month's AI bill.
DSP-Eclipsys helps you bring visibility, accountability and control to both cloud and AI costs. Our managed FinOps services combine expert advisory, proven governance frameworks and intelligent cost optimization across Oracle Cloud Infrastructure, multi-cloud environments, and your broader AI estate.
With our FinOps tool, that same discipline extends down to every token, request, workload and model call. We help connect AI consumption to the teams and business outcomes behind it, so spend has an owner, budgets have guardrails, and optimization becomes an ongoing practice rather than a reaction to an unexpected bill.
Why Cloud and AI Cost Optimization Matters
Cloud costs rarely become a problem overnight. They accumulate as new services launch, workloads scale, providers multiply, and technology teams move faster than traditional financial processes can keep pace.
AI introduces the same challenge, but at a much faster and less predictable pace. A model change, longer prompt, retry loop, or AI agent making additional calls can materially affect costs almost instantly. Consumption is variable by design, and spend can be distributed across the entire AI estate: from models and tokens to applications and agents, GPU and cloud infrastructure, enterprise AI licenses, and the supporting services behind them.
Without real-time visibility and financial governance, organizations often run into the same challenges:
-
Unexpected increases in cloud and AI spending
-
Limited visibility into where money is being spent
-
Difficulty allocating costs to a team, application, model or workload
-
Idle or oversized infrastructure and premium models used where lower-cost alternatives could deliver the same outcome
-
Inaccurate or unreliable cloud and AI cost forecasting
-
Provider invoices that show what was spent, but not who owns it or why
-
Optimization insights, approvals, and remediation scattered across disconnected tools and teams
If any of these sound familiar, you're not alone. As cloud and AI consumption grows, financial management can no longer be an after-the-fact exercise. Organizations need continuous visibility and governance to understand where money is going, hold the right teams accountable, and optimize spend without slowing innovation.
Six Signs Your Cloud and AI Costs Could Be Optimized
Cloud and AI Spend Is Growing Faster Than Visibility
Visibility Drives
Cost Control
You can't optimize what you can't see.
Idle Resources Bleed Budgets
Tagging Creates Accountability
Forecasting Prevents Budget Surprises
Multi-Cloud Creates Complexity
What Is Managed FinOps?
FinOps is more than a cost management tool.
It's an operational framework that brings Finance, Engineering, and Operations together to make better cloud spending decisions.
At DSP-Eclipsys, we deliver Managed FinOps by combining:
-
Experienced Oracle Cloud specialists
-
Proven FinOps processes
-
Continuous governance
-
Cloud and AI optimization expertise
-
Intelligent reporting and analytics
Unlike one-time cloud assessments, Managed FinOps is an ongoing practice that helps organizations continuously monitor, optimize, and govern cloud and AI spend.
Our Managed FinOps Framework
Track & Monitor
Gain complete visibility into cloud and AI consumption.
Analyze & Allocate
Understand where costs belong.
Optimize & Rightsize
Identify waste and improve utilization.
Govern & Automate
Create policies that maintain control.
Predict & Forecast
Use historical trends to improve financial planning.
What We Deliver
Cost Visibility & Reporting
-
Resource and workload-level visibility
-
Cloud, model and token cost allocation
- AI application and agent cost attribution
- Chargeback/showback
-
Historical usage and cost reporting
Right-Sizing & Waste Removal
-
Idle resource detection
-
Infrastructure rightsizing
-
Token and prompt optimization
-
Model selection and routing optimization
-
GPU utilization optimization
-
Licensing optimization
Governance & Tagging
-
Tagging and allocation strategies
-
AI budgets and quotas
-
User and agent spending controls
-
Forecasting
-
Cloud and AI anomaly alerts
FinOps Advisory & Enablement
-
FinOps assessments
-
Roadmaps
-
Oracle licensing reviews
-
Finance & engineering enablement
Why DSP-Eclipsys?
15+
300+
years as an Oracle Partner.
client engagements.
4
FinOps Certified Practitioners
Oracle CMSP/CSP
Oracle Cloud Managed Services
Cloud Health Check
Gain a comprehensive view of your Oracle Cloud environment with expert recommendations to improve security, performance, governance, and cost efficiency.
Finomics Platform
Oracle Cloud Cost Optimization
Finomics Case Study | From Multi-Cloud Complexity to Clarity and Control
See how Finomics helped a global health and nutrition enterprise bring greater visibility and financial control to an estate spanning six cloud environments and more than 45 SaaS platforms, representing approximately $80 million in annual cloud and SaaS spend.
Within the first 90 days, Finomics identified more than $500,000 in annualized savings opportunities across Azure and AWS alone, while helping the organization establish a unified view of cloud and SaaS consumption.
$500K+
Annualized savings opportunities identified in the first 90 days
6
Cloud environments unified
36+
SaaS platforms integrated in four months
DSP-Eclipsys and DSP: Trusted by the biggest names in the industry
How We Help You Get Cloud and AI Spend Under Control
Dashboards can tell you what you spent. Controlling that spend requires understanding what drove it, who owns it, what happens next, and where you can optimize without compromising performance.
DSP-Eclipsys brings AI and cloud costs into a continuous FinOps cycle: understand, attribute, forecast, govern, optimize, and act.
-
Understand and attribute. Connect token, request, application, cloud, and GPU costs to the teams, applications, models, and workloads driving them. Normalize usage into comparable unit economics, such as cost per million tokens, to support showback, chargeback, and better decision-making.
-
Forecast and budget. Set budgets and financial guardrails across teams and organizational levels, forecast token consumption and costs, and understand potential budget impact before the invoice arrives.
-
Govern with controls. Establish quotas and spending controls for users, applications, and AI agents. Detect anomalies early and alert the right owners through Slack, Microsoft Teams, and email before unexpected usage becomes an unexpected bill.
-
Optimize and act. Turn cost insights into measurable action. Reduce unnecessary token consumption through prompt optimization, route workloads to the most cost-effective model for each task, and identify opportunities for model or version migration. We assess your actual usage, workloads, and performance requirements to identify where optimization can deliver the greatest value, without compromising business outcomes.
René Antunez
Field Chief Technology Officer
Database and Cloud
Explore the Technology Behind Our Managed FinOps Services
Our Managed FinOps service is supported by the Eclipsys FinOps Portal and our partnership with Finomics, providing unified visibility, forecasting, anomaly detection, and actionable recommendations across your cloud and AI estate, from infrastructure and licenses to models, tokens, applications, and agents.
Cloud, AI and FinOps Cost Optimization FAQs
What is FinOps, and how does it help manage cloud and AI costs?
FinOps is an operational framework that brings technology, finance, engineering, and business teams together to maximize the value of technology investments. For cloud and AI, FinOps provides the visibility, accountability, forecasting, governance, and optimization practices needed to understand where money is being spent, who owns that spend, and how it can be optimized without slowing innovation.
What is cloud cost optimization?
Cloud cost optimization is the ongoing process of reducing unnecessary cloud spending while maintaining the performance, availability, and scalability your business requires. It can include rightsizing resources, eliminating idle infrastructure, optimizing licensing and pricing models, improving cost allocation, setting budgets, and continuously monitoring usage across OCI, AWS, Azure, and multi-cloud environments.
DSP-Eclipsys combines these optimization practices with FinOps governance to help organizations move from reactive cost cutting to continuous cloud financial management.
What is AI cost optimization, and how does FinOps apply to AI?
AI cost optimization applies FinOps principles to the unique economics of AI. It helps organizations understand, allocate, forecast, govern, and optimize spending across models, tokens, applications, AI agents, GPUs, cloud infrastructure, enterprise AI licenses, and supporting services.
Unlike traditional cloud workloads, AI consumption can change rapidly based on model selection, token usage, prompts, application design, and agent behavior. FinOps provides the financial visibility and governance needed to connect that consumption to the teams, workloads, and business outcomes creating it.
How can organizations reduce AI and LLM token costs?
Organizations can reduce AI and LLM costs by monitoring token consumption, optimizing prompts and context, selecting the right model for each workload, reducing unnecessary requests and retries, controlling agentic AI usage, and identifying anomalies before they become significant expenses.
Effective optimization also means looking beyond the cost per token. The goal is to determine which combination of model, infrastructure, and usage delivers the required performance and business outcome at the most efficient cost.
What are Managed FinOps services, and when should an organization use them?
Managed FinOps services provide ongoing expertise, governance, tooling, and optimization to help organizations manage technology spending more effectively. Rather than relying on periodic cost reviews, a Managed FinOps approach continuously monitors cloud and AI consumption, identifies optimization opportunities, improves forecasting and allocation, and helps teams act on recommendations.
DSP-Eclipsys provides Managed FinOps across Oracle Cloud Infrastructure, AWS, Azure, multi-cloud environments, and AI workloads, helping organizations establish financial accountability while continuously optimizing technology spend.
Our Thinking
Cloud
FinOps in the Age of AI: Why Visibility Is No Longer Optional
Chanaka YapaJul 24, 2026, 3:00:00 PM
OCI
FinOps Is a Catalyst for Innovation
As cloud has been adopted over these past 15 years, organizations are under increasing pressure to optimize cloud spend while still driving...
Gustavo Rene AntunezJun 26, 2025, 12:00:00 AM
Let's Talk About Your Cloud and AI Costs
Every cloud environment is different. Our Cloud and AI Cost Optimization Assessment provides a tailored review of your current estate, helping you identify opportunities to improve visibility, strengthen governance, reduce waste, and optimize cloud and AI spend. Complete the form below and one of our specialists will be in touch.