NewInfrastructure governance

Ecosystem for software and hardware, leveraged by humans and by agents.

One control plane for the environments, infrastructure and compute your teams contend over — with the approvals, quotas and cost attribution that make it safe to hand any of it to an agent.

Running in production at

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The operating layer for self-service infrastructure

Approve, provision, govern and optimize infrastructure across environments through one operational layer — with agentic operations, multi-cloud FinOps, and AI-generated dashboards from natural-language requirements.

Realm9 dashboard view
18 environments live

Stop losing days to environment contention

Six teams, one integration environment, and a spreadsheet nobody trusts. Realm9 replaces it with a real booking system — requests, priority queues, approval chains, and a calendar that reflects what is actually happening.

  • Priority-ordered queues with conflict detection before the clash, not after
  • Approval workflows that route by environment class, cost or blast radius
  • Automatic reclaim when a booking lapses, with owner notification
  • A shared calendar your release manager and your CI system both read
Realm9 Requests page showing the booking priority queue with approval status for Booking 1, 2 and 3

One control plane for infrastructure you own and infrastructure you rent

Terraform runs, state locking, drift detection and policy scanning — across AWS, Azure, GCP and OCI, and across the vCenter and Proxmox estates most modern tools quietly ignore.

  • Plan, apply and destroy with policy gates from Checkov, Trivy and TruffleHog
  • Drift detection with remediation plans you review before they run
  • Remote state with locking, versioning and per-workspace RBAC
  • On-prem parity: the same workflow for a VM in your rack and an instance in us-east-1
Realm9 Terraform run showing a completed plan and apply with policy checks and outputs

Cost you can explain, not just cost you can see

Every FinOps tool can tell you what AWS charged. Realm9 can tell you which agent, running which task, on behalf of which team, under whose approval, caused the charge — across cloud, on-prem and model tokens.

  • Unified spend across public cloud, private data centre and LLM providers
  • Anomaly detection tied to the request that triggered it
  • Rightsizing and idle-reclaim recommendations with one-click, audited action
  • Chargeback and showback reports finance will actually accept
Spend by principal · last 7 days
team/data-science
$22,410 ▲41%
team/platform-eng
$9,860
agent/ci-migrator
$4,118
agent/pr-reviewer
$1,244
mediumAnomaly · data-science exceeded GPU budget on 09-11
Causelease r9-lse-8102, 8×H100, no TTL set
Policy appliedgpu-max-ttl now enforced

Give platform teams one place to govern the work they support

Start with the workflow that creates the most friction today, then connect environment access, Terraform operations and cost controls as your estate grows.