It acts as your 24/7 FinOps analyst, constantly scanning for waste, anomalies, and optimization opportunities across your cloud infrastructure.
Identifies stopped EC2 instances, unattached EBS volumes, and old snapshots that are quietly draining your budget.
Detects sudden spikes in spending (e.g., massive data egress) and alerts you immediately with the root cause.
Analyzes CPU/Memory utilization trends to identify resources that are larger than necessary and recommends rightsizing.
Audits resources for required cost allocation tags and reports (or auto-tags) non-compliant resources.
Analyzes usage patterns to recommend the optimal mix of Reserved Instances and Savings Plans for maximum ROI.
Breaks down K8s cluster costs by namespace, service, and pod to show exactly which team is driving spend.
Unified view of costs across AWS, Azure, and GCP in a single dashboard, normalizing data for apples-to-apples comparison.
Can be configured to automatically stop idle dev instances at night or cleanup old images based on policy.
Predicts end-of-month spend based on current run-rates and alerts stakeholders before budgets are blown.
Seamlessly integrates with major cloud providers and FinOps tools.
AWS, Microsoft Azure, Google Cloud Platform (GCP)
Kubernetes, EKS, AKS, GKE, ECS
Terraform, AWS CloudFormation, Ansible, Pulumi
Slack, Microsoft Teams, PagerDuty, Email
Grafana, Datadog, QuickSight, Tableau
Jira, ServiceNow, Asana, Trello
Jenkins, GitLab CI, GitHub Actions, CircleCI
Snowflake, BigQuery, Redshift, Databricks
Open Policy Agent, Chekov, Bridgecrew, Cloud Custodian
See how companies are taking control of their cloud budgets.
Monthly Savings
Problem: Rapid growth led to unchecked resource spawning. Devs spun up large EC2s and forgot them. Solution: Cloud Cost Agent identified 200+ idle instances and unused RDS db's.
"It paid for itself in the first hour. We had no idea we were burning $15k/month on zombie servers."
— VP of Engineering
Zero Waste
Problem: Manual RI purchasing was too slow, leading to low coverage and wasted on-demand spend. Solution: Agent automates RI/Savings Plan purchasing based on sustained usage.
"Our coverage jumped from 60% to 95% without me having to stare at spreadsheets all day."
— Cloud Architect
Network Efficiency
Problem: Unexpectedly high egress fees across regions. Solution: Agent traced traffic and recommended CloudFront caching and VPC peering optimizations.
"We were bleeding money on cross-region traffic. The agent pinpointed the exact services responsible in minutes."
— CTO
Dynamic Scaling
Problem: Over-provisioning "just in case" led to massive waste. Solution: Agent managed predictive scaling policies based on real-time demand.
"We handled record traffic with 20% fewer instances than last year thanks to smarter auto-scaling."
— DevOps Lead
Get full visibility and maximize your cloud ROI with the AI Cloud Cost Optimization Agent.