Cloud Sleuth is the ownership and context layer for your cloud. It answers who owns each resource, what it's actually for and whether it should still exist, so you can cut waste instead of just reporting on it.
Runs on your machine or VPC Read-only Nothing leaves your environment
01 / question
A maintained ownership model, not a tagging aspiration: teams, services, cost centers and environments, with full history.
02 / question
Living inventory with relationships and purpose, so you can see what a resource supports before you touch it.
03 / question
Policies that check ownership, purpose and hygiene against the live estate and send findings to the people who own them.
The problem
Rightsizing and idle-resource detection are the low-hanging fruit. The waste that sticks around comes from resources nobody can confidently claim, explain or safely remove.
The platform · Cloud Sleuth Cloud
Virtual tagging, continuous inventory with topology, and policy as code usually live in separate products. Cloud Sleuth Cloud, in development, puts them on top of an ownership model that is maintained continuously. The free local tool covers the basics on AWS and Azure.
core / ownership model
Teams, services, cost centers, environments and business units, assigned at any level and derived from native tags, virtual tag rules, your service catalog or by hand. Every change is audited, and shared resources are handled explicitly.
01 / allocation
# illustrative rule: data-team-by-name match: name: "etl-*" set: team: data cost_center: CC-410
Stamp ownership onto cost without touching infrastructure, even where native tags are missing or can't exist.
02 / context
A living inventory with relationships, so you see what a resource supports before anyone deletes or rightsizes it.
03 / governance
# illustrative policy: require-owner applies_to: all when: owner is missing route_to: account owner exceptions: expire in 30d
Rules in Git, checked continuously against the live estate, with findings routed to the team that owns them.
Context before action
Cost tools say a resource looks idle. Cloud Sleuth shows who owns it, what depends on it and which rules it breaks, so cleanup doesn't become an outage, or another ignored alert.
team-data
suggested by virtual tag rule · name etl-*
Nothing currently depends on it
no inbound connections in 61 days · 1 attached volume
2 open policy findings
missing-owner · idle · routed to team-data
How it works
A single binary or Docker container that runs on your machine or in your VPC. Join the early-access list and we'll email you when it's ready.
It inventories a handful of AWS accounts and Azure subscriptions with read-only access and applies simple ownership rules by account, subscription and name pattern. Nothing leaves your environment.
Unowned resources, common orphans and basic allocation gaps, in minutes. When you need it across every account and team, that's Cloud Sleuth Cloud.
Free local tool vs. Cloud Sleuth Cloud
The free local tool proves the core insight on your own AWS and Azure accounts. Cloud Sleuth Cloud turns it into a collaborative, scalable and enforceable platform.
Both are in development. The early-access list hears first.
Who it's for
Companies spending roughly $50k to $2M+ a month on cloud, where one person or a small platform team owns cost, native tools and spreadsheets have run out of road, and enterprise FinOps platforms feel too heavy.
Needs
Understand the estate, enforce standards, reduce ownership ambiguity
Gets
Living inventory, topology and policy as code with ownership routing
Needs
Allocate 100% of spend and drive accountability
Gets
Virtual tags, shared-cost allocation and unallocated-spend tracking
Needs
See what their team owns and what is safe to clean up
Gets
Team-scoped views, ownership findings and context before action
Needs
Trustworthy showback and chargeback
Gets
Allocated cost reports tied to a maintained ownership model
Case studies
Idle VMs, abandoned databases and storage nobody was accountable for, and how each one was found and resolved.
$9k/month cut from a $30k/month Azure subscription.
An anonymized case study: 89 Azure VMs left over from an acquisition ran at near-zero CPU for six months, costing a technology startup $18,400 a month. How they were found, verified and removed.
An anonymized case study: seven Azure SQL databases left behind after a migration cost a financial services company $12,600 a month. How they were verified as unused and removed without risk to production.
An anonymized case study: 23.2 TB of S3 data had gone untouched for more than two years, and much of it had no clear owner. How access analysis and owner interviews moved it to Glacier Deep Archive without deleting a file.