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Cloud cost optimisation agents

Cross-industry · A multi-cloud enterprise estate

FinOps agents that detect waste, propose remediations, and execute pre-approved changes under guardrails across AWS, Azure, and GCP.

The problem

  • Cloud spend was growing faster than revenue with no clear single owner.
  • Optimisation recommendations from native tooling were ignored because they lacked context.
  • Manual remediation could not keep pace with the rate of new workloads.

The architecture

  • Discovery agents correlate billing data with workload owners, tags, and recent deployments.
  • Recommendation agents propose remediations with explicit cost / risk trade-offs.
  • Execution agents apply pre-approved low-risk changes; everything else is routed to a human approver via chat ops.
AWSAzureGCPTerraformLangGraphSlack

The outcome

  • FinOps moved from a quarterly review to a continuous, agent-led practice.
  • Engineering teams received recommendations in their own language and chat tools, with full reasoning.

Services drawn on

A similar problem on your roadmap?

A Discovery Sprint is the fastest path to a scoped, costed proposal.

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