Operations | Monitoring | ITSM | DevOps | Cloud

Shipped: Personalized cost access, powered by SSO

Instead of building a separate role for every team, region, or department, admins can create a single role that automatically personalizes access for each user based on their SSO attributes. Someone moves teams or a new group gets created, and the new access takes effect at their next login with no CloudZero configuration. As AI spend grows, more companies are looking to give teams visibility into their own AI costs without exposing every individual’s usage across the org.

The finance dashboard I actually use, built from CloudZero and Campfire in an afternoon

Every finance person I know lives in the same loop approaching the end of the month, quarter, or fiscal year. Leadership wants to know where the financials will land (most times before the close has occurred). CS wants customer margins. Someone on the People team needs each department’s AI spend for an OKR review, and they need it quickly to make business decisions. Each answer sits in a different tool or a different spreadsheet, and I bounce across all of them several times a day.

Shipped: In-app help, right beside your work

You are mid-investigation, chasing a spike or pulling a number for finance, and you hit a term or a workflow you need to look up. You should not have to lose your place to find an answer. Guide lives in a fixed spot in the left sidebar, always one click away. It opens a panel on the right side that sits beside your page instead of covering it. Your chart, filters, and time range stay exactly where they were. Nothing gets rebuilt and you keep the thread of what you were investigating.

Your FY27 plan deserves a real AI number, not a hedge

Budget season is starting and most finance teams are finding the AI line is the most evasive line on the page. You lived through the year. AI spend came in higher than planned and moved in ways nobody could foresee or forecast. And when the board asked what it produced, the honest answer probably was “we’re working on it.”

Shipped: Codex spend tied to the work behind it

People run Codex on their own laptops. When Codex is signed in with a ChatGPT subscription, OpenAI’s own admin console shows who used it and how much: messages and credits. What it doesn’t show is what any of that usage was for, or how it compares to what your team spent on other AI tools. The CloudZero desktop agent for macOS installs on a Mac, sees the traffic from AI coding tools, and prices what those tools use.

Why is AI so expensive? The real cost drivers of AI

AI is expensive because the model bill is only part of the cost. Three components set the floor: model subscriptions, per-token API pricing, and infrastructure. Three more make it move: adapting models to your business, catching and fixing errors, and rising energy and datacenter costs. Efficiency doesn't fix it, because cheaper AI gets used more, not less. Businesses are willing to spend on AI. Research from Deloitte found that in 2025, 85% of organizations increased their AI investments.

Shipped: Monthly cost comparison in Explorer gets a glow up

Months have different numbers of days, and a monthly cost chart built on raw totals mixes that calendar difference into the trend. A 28-day February next to a 31-day March shows a 10.7% increase even when daily spend never moved. The same math works in reverse: real growth in a short month can look flat, hiding an increase worth investigating. That costs you time in two places. The first is triage.

AI budgeting: how to plan and forecast AI spend

AI budgeting is the process of planning, allocating, and forecasting an organization's AI spend: model and API costs, AI infrastructure, tooling, and the people running it all. It differs from traditional budgeting because AI spend is usage-based, scales with product success rather than headcount, and often spans multiple providers.

Shipped: Cost anomalies and savings recommendations, delivered into ServiceNow

If your engineering teams run on ServiceNow, incidents are where they get work done. Putting cost work into an incident gives it the same path to resolution as any other work item your team handles. When a cost anomaly arrives as an incident, your teams route it, assign it, and resolve it on their usual SLAs. When a savings recommendation arrives as an incident, an engineer owns it and acts on it. Now you can send either straight into ServiceNow.