AI-Powered Forensics for Your Cloud Spending
Cloud Sleuth’s Pattern Analysis feature uses advanced AI and machine learning to uncover hidden relationships and waste patterns in your cloud infrastructure that human auditors would never catch. Like a detective connecting evidence at a crime scene, we reveal the full story behind your cloud costs.
Key Capabilities
🧠 AI Forensics Engine
Our proprietary AI analyzes millions of data points to identify spending patterns, usage anomalies, and optimization opportunities that traditional tools miss.
🔗 Cross-Resource Correlation
Discover how resources interact and depend on each other. Understand the true cost impact of architectural decisions across your entire stack.
📈 Trend Detection
Spot concerning trends before they become expensive problems. Our pattern recognition alerts you to gradual cost creep and usage anomalies.
🎯 Waste Pattern Recognition
Identify common waste patterns like over-provisioning, zombie resources, and inefficient architectures based on analysis of thousands of cloud environments.
How It Works
- Data Collection: Gather comprehensive telemetry from all your cloud resources
- Pattern Recognition: Apply machine learning models trained on millions of cloud environments
- Correlation Analysis: Connect usage patterns across services, regions, and accounts
- Insight Generation: Transform complex patterns into actionable recommendations
Patterns We Detect
Common Waste Patterns
- The Weekend Ghost: Resources that sit idle on weekends but run at full capacity
- The Forgotten Experiment: Development resources that outlived their purpose
- The Overprovisioned Giant: Resources running at <10% capacity continuously
- The Orphaned Assets: Storage, snapshots, and IPs disconnected from any active service
Architecture Inefficiencies
- The Redundant Stack: Duplicate services running the same workload
- The Legacy Trap: Old infrastructure running alongside new, doubling costs
- The Region Sprawl: Unnecessary multi-region deployments for local applications
- The Backup Black Hole: Excessive backup retention costing more than primary storage
Real-World Impact
Case Study: The Hidden Dependencies
A SaaS company was puzzled by their growing cloud costs despite stable user numbers. Our Pattern Analysis revealed:
- 15 interconnected services were scaling together unnecessarily
- A misconfigured auto-scaling policy was triggering cascade effects
- $30,000/month was being wasted on this invisible pattern
Within 48 hours of detection, the issue was resolved, saving $360,000 annually.
Benefits
- See the Invisible: Uncover waste patterns that are impossible to spot manually
- Predictive Insights: Anticipate future cost issues before they materialize
- Data-Driven Decisions: Make architectural choices based on actual usage patterns
- Continuous Learning: Our AI improves with every environment it analyzes
Getting Started
Pattern Analysis begins working immediately after your initial resource discovery. Our AI starts learning your unique patterns and typically delivers first insights within 24 hours. No configuration needed – just let our forensics engine do its work.
Ready to see what patterns are hiding in your cloud? Let Cloud Sleuth connect the dots.