Cloud & AI Spend Governor
A FinOps-inspired platform for analyzing cloud and AI spending, detecting cost risks, simulating optimization scenarios, and generating actionable cost-control recommendations.
Product overview
Why this product exists.
Cloud & AI Spend Governor analyzes local infrastructure inputs, applies policy-aware checks, and produces structured findings for the CLI, dashboard, SARIF, and GitHub Actions annotations.
Problem / motivation
Cost feedback often arrives after deployment. This project explores how teams can surface understandable cost and policy findings earlier in the delivery workflow using local, reproducible inputs.
Product experience
Key features.
- 01
Shared structured findings across CLI and dashboard outputs
- 02
SARIF reports and GitHub Actions annotations
- 03
Local scenario and policy-based analysis
Under the surface
Architecture and technical challenges.
Challenges
- Keeping each finding explainable across human and machine-readable outputs
- Separating simulated/local pricing inputs from claims about live cloud billing data
Technology stack
Delivery status
What exists today.
Implemented
- — Structured findings
- — CLI output
- — SARIF
- — GitHub annotations
Experimental
- — Local pricing and policy scenarios
Honest edges
Limitations and what comes next.
Known limitations
- Pricing catalogs and scenarios are local or demo-based; the project does not claim live cloud account scans.
Future improvements
- Broaden infrastructure format coverage
- Add richer decision-comparison views