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By David Aponovich
There’s a good interview making the rounds. BizTech sat down with IBM’s James Stevenson to talk about how financial institutions can get a handle on cloud and AI costs. The advice is solid: get visibility, kill idle resources, tighten governance, tag everything. And pull finance and engineering into the same room. I don’t disagree with it. But I read the whole piece and noticed where the gravity pulls: control costs, reduce waste, bring down spend. The headline says it (‘Q&A.
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By Thomas Evans
If you route model traffic through Bifrost, you already have the hard part: one place every AI call passes through, where the model, the tokens, and the cost are visible on the way past. It’s the cheapest spot in your stack to measure AI spend. What’s missing is everything downstream – today that usage only becomes “spend” weeks later, when the provider invoice lands as a lump sum you can’t break apart.
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By Sharon Pollard
A year ago, the sentence “I just deployed an app on GitHub” wouldn’t have made sense coming from me. I’m the VP of People at CloudZero; code deployments and I were not close friends. That’s changed. In this AI era, non-engineers are building, and I think that’s a genuinely good thing. But only if it’s tied to something that matters.
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By Scott Castle
If you run Claude through LiteLLM, some of that spend is probably going uncounted – and you can’t see it, precisely because the data isn’t there. Routing through a gateway is messier than it looks: LiteLLM alone can carry Claude several ways – the OpenAI-compatible endpoint, and the Anthropic pass-through proxy that the native SDK and Claude Code use – and each path describes the same call differently.
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By Dan Reichert
We rebuilt docs.cloudzero.com from the ground up. The result is a documentation site organized around what you’re trying to accomplish rather than feature names and jargon.
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By David Aponovich
On June 18, OpenAI gave ChatGPT Enterprise admins new credit usage analytics and spend controls. It’s a single view of credit consumption broken down by user, product, and model, default workspace budgets, per-group limits, and a Cost API for pulling the data into their own systems. Two days earlier, Microsoft shipped Copilot Cowork with spending limits, budget allocation, usage alerts, and user-level caps. This is a step in the right direction.
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By Lyne Carolyne
Customer lifetime value (CLV) is the total revenue a business expects from a single customer over the entire relationship, minus the costs of serving them. The standard SaaS CLV formula: Average Revenue Per Account x Gross Margin % / Monthly Churn Rate. For a $500/month customer with 75% gross margin and 5% churn: CLV = $7,500. That number can swing materially once AI spend per customer is built into gross margin, something many SaaS companies still don't do.
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By Brady Lenahan
Point A: 1835. Andrew Carnegie is born in a weaver’s cottage in Dunfermline, Scotland. The cottage has one main room, which the Carnegies share with another family. Point B: 1901. Andrew Carnegie becomes the richest man in the world when Carnegie Steel Company wins the Iron vs. Steel industrialists’ war, and he sells the company to J.P. Morgan for the modern equivalent of $450 billion.
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By Kevin Lamb
The Anthropic Enterprise connector pulls per-user Claude Enterprise cost and usage into CloudZero, so you can allocate Claude spend to the teams that drove it.
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By Kaitlin Woo
The core of ROI is visibility. If you can clearly see … 1. What it costs to produce the thing you make, and 2. How much money it makes you … then calculating ROI is easy. But with AI, as with the cloud before it, getting that visibility is extremely challenging. Why? Because the cost data associated with each is inherently chaotic.
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With CloudZero you get insights about your applications and systems, helping you manage operations at a scale that you’ve never had before. Our platform provides you with insights about every piece of your system, including the real cost of resources, resource utilization, reserved capacity and cost center efficiency.
With the accurate and trusted data provided by CloudZero you can minimize or eliminate under utilized resources, visualize costs for easy comprehension and oversee the entire software lifecycle. Nothing is out of view when using CloudZero’s Observability platform. From regional views to individual resources, you have insights at every level to help you keep your systems running smoothly.
How do we do it?
- Collect and Normalize: CloudZero’s platform starts by collecting the data from your CloudWatch, CloudTrail, VPC Flowlogs, Lambda Data Events and Billing Data from every AWS account you connect. This part of the platform is isolated in its own account for security and has read-only access to the accounts you connect.
- Populate the Stream: All of the data collected is normalized and the events, resources, statistics and billing data are organized into data streams which allow our platform to perform real-time analytics on all the data collected.
- Find Meaning: Our algorithms take in the normalized data and perform complex analytics sifting through all the data to filter noise and enhance signal. We use Machine Learning on a large scale to learn what is valuable to surface.
- Visualize Everything: The application provides opinionated visualizations of the insights determined by the platform’s AI. From regional system maps to single resources to cost of service broken down by team, CloudZero’s platform provides true observability to everyone in your organization.
Observability for Everyone. Add cost as a first-class metric and understand the financial effect of operational decisions.