Manage Cloud with AI

Cloud bills don't break loudly — they bleed. An EC2 fleet that outgrew its workload months ago, a dev environment nobody turned off, load balancers orphaned by deleted clusters, snapshots accumulating since the quarter started, and a Savings Plan that expired last week. Whether you run a single AWS account, an Azure landing zone with a dozen subscriptions, GCP projects across regions, or all three at once — VibeComputing handles the full spectrum of cloud operations: cost and usage analysis, rightsizing, idle-resource sweeps, tagging and governance, security posture, and commitment planning. Stop exporting CSVs into spreadsheets. Just describe the problem.

The agent connects in seconds and immediately maps the landscape — accounts and organizational structure, spend by service and tag, utilization against provisioned size, security groups and exposure, and coverage against your reserved capacity. "Why is this month's bill up 38%?" "Show me everything idle and what it costs to keep." "Which instances are pegged at 3% CPU for 30 days?" "What would a 3-year commitment on this RDS family actually save?" The AI walks Cost Explorer, utilization metrics, and inventory like a FinOps engineer — correlating the spend spike with the forgotten autoscaling floor, the waste with the team that left — and proposes the fix before it touches anything.

For platform and cloud teams, VibeComputing fits existing workflows without ceremony. The zero-trust outbound-only agent model works inside locked-down environments — no IAM role changes beyond read, no credentials exposed to the internet. Read-only by default; every proposed mutation is shown as the exact CLI command or API call before it runs, and sensitive identifiers are obfuscated before they ever reach a model. Combined with LLM data obfuscation for compliance-heavy environments and BYOK for strict control over your AI provider, it's the most secure way to manage cloud with AI.