The most challenging question in AI today isn’t how to build with it. It’s whether you can prove it’s worth what you’re spending on it.
Every week, I hear the same thing from engineering and finance leaders: “We know the AI bills are big. We don’t know if they’re worth it.”
In fact, according to CloudZero’s original research, about 50% of organizations investing in GenAI readily admit they can’t confidently calculate ROI on their AI initiatives — what they’re actually spending and, more importantly, whether their new favorite investment is actually paying off.
And that’s just the teams willing and brave enough to admit to their lack of a strong ROI. The rest likely don’t want to say it out loud. Based on conversations I have with folks daily, the reality is even starker than that.
That’s why we moved quickly when Anthropic released their Usage & Cost Admin API. CloudZero is now the first cloud cost platform to integrate directly with it.
This means our customers can ingest, allocate, and analyze Claude usage alongside every other cloud, AI, PaaS, and SaaS cost they’re already tracking — finally putting AI spend into the same frame of reference as the rest of their business.
That’s why we moved quickly when Anthropic released their Usage & Cost Admin API. CloudZero is now the first cloud cost platform to integrate directly with it.
Understanding Unit Economics In The Age Of AI
AI isn’t experimental anymore. It’s part of the stack. Companies are weaving large language models into products, workflows, and customer experiences at a pace that rivals the early days of cloud.
The mounting problem is cost. AI doesn’t behave like traditional infrastructure. A small change in prompt design, context length, or inference volume can swing spend wildly. What looks efficient in dev can balloon in production. And unlike compute or storage, you can’t eyeball usage and guess the bill.
That’s why unit economics matter. Instead of just seeing a total invoice, you need to know:
- Cost per token type or model family
- Cost per workspace or feature
- Which teams and workflows are delivering the most value per dollar
When you break spend down this way, AI stops being a black box expense. It becomes measurable. You can see which teams are efficient, which workflows are wasteful, and where cost is directly tied to business value.
So when Anthropic announced its new Usage & Cost Admin API with observability tools in mind, we knew we had to act fast to bring that same data into CloudZero. Now, customers can explore trends, detect anomalies, and see Claude costs in the same context as the rest of their cloud environment, with the granularity to tie spend back to engineering decisions.
Turning Anthropic Cost And Usage Into Engineering-Driven Insights
Anthropic’s Cost & Usage APIs give you programmatic access to token consumption data by model, workspace, tier, and context window, with precision Anthropic’s console can’t match. You get uncached input, cache hits, output tokens, and tool usage every minute, hour, or day.
That’s powerful data. But raw numbers don’t drive better decisions. Here’s how CloudZero turns those metrics into strategic insight — fast, accurate, and engineer-centric:
1. Unit economics that align with business reality
We transform token usage into cost-per-feature, cost-per-model, or cost-per-workspace — just like every other piece of cloud spend. That means engineering decisions become clear business decisions, whether you’re optimizing caching or swapping model tiers.
2. Full composite visibility alongside all cloud and AI spend
Anthropic costs aren’t siloed. AI costs appear in the same dashboards and alerts as your AWS, Kubernetes, Datadog, or Databricks spend. That single-pane consistency drives clarity and context.
3. Real-time anomaly detection and guardrails
We surface unexpected token spikes or context-window creep with AI-driven alerts — even before finance notices. Engineers see it in Slack or dashboards, with direct attribution to model, workspace, or API key.
4. Attribution to engineering dimensions, not just IDs
We marry workspace and API key usage with product lines, features, and even customer accounts. Claude’s spending then becomes traceable to value, so you can ask not just “What happened?” but also, “Who is responsible and how did that affect ROI?”
Developers, Developers, Developers!
Tracking Anthropic spend is not just about API calls. Claude Code adds a new dimension to the cost picture. Developer usage is not tidy or predictable. It shifts as teams try new prompts, stretch context windows, and rewire workflows. The tempo is fast.
For years, I have said every engineering decision is a buying decision. With AI coding assistants, that line is literal. Every line of code generated is bought and paid for. Costs move quickly, so every AI choice is now a purchase.
Treating developer AI tools as real cost signals opens a new lane. We can now measure the cost to create software, not only the cost to deploy, maintain, and deliver it. Leaders can weigh productivity gains against clear dollars, tie spend to features and teams, and see how build decisions shape outcomes.
How Customers Gain Visibility Into Claude Costs With CloudZero
CloudZero ingests Anthropic’s Admin API data alongside all your existing cloud, PaaS, AI and SaaS costs, bringing order and clarity to what would otherwise be an unimaginably complex picture.
This unified and normalized view transforms raw usage data into definitive answers, making it possible to see exactly how Claude spend aligns to product features, business units, and customer value. For the first time, engineering and finance leaders can stop simply tracking spend and instead focus on proving value.
With CloudZero, customers can:
- Directly ingest, normalize, and explore Claude spend alongside the rest of your cloud and AI spend
- Track token usage trends across inputs and outputs
- Break down cost by model, workspace, service tier, and more
- Map spend to ownership structures such as product lines or feature teams
- Spot inefficiencies, such as unusually high token usage for specific workflows
- Set alerts for sudden spikes in usage or spend to go directly to the responsible team
With Claude becoming a central AI building block, from Claude Code in dev workflows to enterprise LLM features, understanding spend is non-negotiable. CloudZero now helps engineering teams close the loop, providing fully attributed, granular spending visibility for Anthropic alongside your broader cloud costs.
Want to see it in action? Schedule a demo now and discover how to drive smarter, cost-balanced AI innovation.
The Cloud Cost Playbook
The step-by-step guide to cost maturity
