Overview of AI Hub

Ask questions about your costs in plain English and get answers that connect spend to the teams, products, and outcomes behind it, including the ROI of your AI investments. AI Hub connects to your full cost picture across every cloud provider, SaaS platform, AI platform, and custom source in your account. Built on the Model Context Protocol (MCP), it works from Claude Code, Cursor, VS Code, GitHub Copilot, and a growing list of AI tools.

AI Hub in action

Your cost data does not live in a silo. Through MCP, your AI tool connects to CloudZero alongside your git repositories, observability platforms, ticketing systems, and sales data at the same time. Cost, engineering, operations, and business context in a single conversation.

• VP of Finance requests a customer profitability analysis ahead of a board meeting. The FinOps analyst asks "Show me the cost to serve our top 10 customers and compare it against their contract value." AI Hub pulls cost data across customer Dimensions while the Salesforce MCP server retrieves contract values from opportunity records. The result is a per-customer profitability view that connects cloud spend to revenue, ready for the deck in minutes instead of days.

• FinOps lead starts the morning with a cost check. Asks "What changed in our spend this week?" AI Hub surfaces a compute cost increase and traces it to a specific account. The AI tool then checks git history, identifies the pull request that caused it, and compares against last month's baseline across team Dimensions. The lead shares the analysis to Slack with a recommendation for the owning team.

• Engineer reviews a Terraform change before merging. Asks "What will this cost?" AI Hub reads the module, maps the new resources to current CloudZero baselines, and projects the monthly impact. The engineer adjusts the instance class, runs the projection again, and merges with confidence.

What you can do

AI Hub includes a library of guided analysis skills that structure investigations into proven workflows. Each skill pulls the right data, compares against baselines, breaks down results across your Dimensions, and surfaces what matters.

For the full list of skills with example prompts and trigger keywords, see the Skills Reference.

Investigate cost changes

Ask why your spend changed. AI Hub compares the change against your baseline, breaks it down by account, service, and region, and surfaces the root cause. When your AI tool is also connected to your git provider, AI Hub can correlate cost changes with recent deployments and pull requests to pinpoint what changed and who changed it.

Analyze spending patterns

Track how costs are trending over days, weeks, or months. AI Hub identifies growth rates, seasonal patterns, and the biggest contributors to your spend, ranked by impact.

Compare costs across any dimension

Compare spending across time periods, environments, accounts, regions, teams, products, or any custom category defined in your Dimensions. AI Hub works with your organization's specific cost structure, not just cloud provider defaults.

Deep dive into specific services

Get detailed breakdowns of individual cloud services, including usage patterns, cost drivers, and service-specific optimization recommendations.

Check tagging quality

Evaluate resource tagging coverage across providers. AI Hub identifies untagged or inconsistently tagged resources that affect cost allocation accuracy and prioritizes what to fix first.

Triage optimization recommendations

AI Hub pulls unaddressed recommendations from CloudZero Optimize, researches each one for context (related infrastructure changes, current utilization, ownership), and ranks them by real-world impact so you act on the right ones first. When your AI tool is connected to additional sources like Slack or Jira, AI Hub can search for related conversations and tickets to identify the right owner.

Estimate infrastructure cost impact from code

Before you deploy, understand what it will cost. AI Hub analyzes Terraform, CDK, CloudFormation, SAM, Serverless Framework, and Pulumi definitions to project monthly costs. It also evaluates code diffs to flag the specific lines of infrastructure code that will affect your spend before they reach production.

Works with your tools

The fastest path is the Claude Code Plugin, which bundles the MCP server with the full set of guided skills in a single install command. See Set Up AI Hub for setup instructions.

AI Hub also works with Cursor, VS Code, GitHub Copilot, Codex, Gemini CLI, Kiro, and more. See Set Up AI Hub for the full list and install instructions.

Browse ready-to-use prompts in the Prompt Catalog

The Prompt Catalog is a library of ready-to-use prompts organized by role (FinOps, Finance, Engineering, DevOps, Product, Executive), maturity level, and use case. Browse prompts and copy them directly into your AI tool.