One platform for every resource: cloud infrastructure across Azure, AWS, GCP, and Oracle, plus AI tool spend on Anthropic, Cursor, and GitHub Copilot — evidence-backed recommendations, gated behind an approval workflow your team controls end to end.
Monthly Spend
$84,230
12.4%
Savings Found
$19,860
auto-detected
Resources
412
4 clouds
Spend vs. Forecast
30dVM rightsizing — 3 nodes
P95 CPU 14d: 11.2%
Disk tier step-down
Premium → Standard SSD
7 orphaned disks & IPs
awaiting approval
Platform capabilities
Every recommendation traces back to actual metrics — Azure Monitor, per-resource cost snapshots, real IOPS/throughput evidence — so your team approves changes with confidence, not guesswork.
A single provider-agnostic connector interface — inventory, cost, and utilization sync behind one contract. Onboarding always runs a live test-connection before a subscription is saved.
Azure
Inventory, cost, VM/disk utilization via Azure Monitor
AWS
Inventory, cost, and utilization sync
GCP
Inventory, cost, and utilization sync
Oracle Cloud
Inventory, cost, and utilization sync
The same evidence-backed pipeline that rightsizes your cloud also covers your AI coding tools — usage, seat utilization, and spend, in one place instead of a dozen billing pages.
Anthropic
Claude API token spend, usage trends, and rate-limit headroom
Cursor
Per-seat usage and idle-license detection
GitHub Copilot
Seat utilization and license spend
Cloud infrastructure and AI tooling in a single pane of glass — one inventory, one recommendation feed, one approval-gated execution path, one audit trail. No swivel-chairing between cloud consoles and AI vendor dashboards.
Real CPU, network, and disk I/O pulled straight from Azure Monitor — reduced with a noise-resistant method and scored for confidence, not a flat threshold guess.
Rightsizing, disk tier, capacity, and orphan cleanup all flow through the same consistent review process — every proposal shows its evidence before you approve it.
Real per-disk IOPS/throughput evidence drives Premium ↔ Standard SSD ↔ Standard HDD step-downs, plus grow-only capacity resize when pressure is detected.
Unattached disks, unassociated public IPs, source-less snapshots, and unattached NICs — surfaced in a dedicated tab with a single approval to reclaim spend.
Host-level VM metrics and true per-disk IOPS/throughput evidence — not a heuristic guess about what's actually running hot or idle.
Real host and service health from Checkmk, plus synthetic checks — HTTP, TCP, DNS, ICMP, TLS, and full browser journeys — in the same inbox as your cloud resources.
Every health change is checked against your alert policy before anything reaches Jira, so your board reflects real, current problems — not a backlog of duplicate tickets and noise from a flapping check.
Propose → approve → execute → audit. Mutating cloud calls are walled off in an execution path unreachable from anywhere else — enforced at build time, not just by convention.
Daily cost snapshots grouped by resource ID, not just service — real per-resource trend lines, not a subscription-wide number.
Scoped roles for every cloud provider — no standing full-permission blast radius on your production identity.
Every mutating action — start, resize, tier change, delete — is logged end to end, with fail-closed handling on execution errors.
Every connection is tested before it's saved. Deactivating a subscription soft-deletes it — historical cost and resource data is never lost.
How it works
Sync
1Analyze
2Recommend
3Approve
4Execute
5Audit
6Pricing
Pricing is tailored to your cloud footprint — tell us what you're running and we'll size it for you.
No seat fees, no egress surprises — every capability below is included from day one.
Tell us about your footprint — we'll reply within one business day.
From the blog
AI Tools
Anthropic API keys, Cursor seats, Copilot licenses — provisioned fast, reviewed rarely. Here is why AI tool spend needs the same rigor as cloud cost, and how to get it.
Monitoring
Checkmk is a serious monitoring engine with a jargon-heavy console. Here is how CloudMint turns it into an alert inbox your team actually trusts.
FinOps
Oversized VMs are rarely a mistake made once. They're the accumulated residue of a dozen reasonable-sounding decisions. Here's where the waste actually comes from.