Simple classification
Route to a smaller, lower-cost model.
/ Cloud & AI Cost Operations
Cloud & AI Cost Operations
Identify infrastructure waste, excessive token usage, and inefficient model selection. Execute approved optimizations with verification and recovery built in.
Idle and oversized cloud resources
Model selection and routing
Token and context budgets
Prompt and response caching
Repeated tool calls and agent loops
Workload scheduling and scaling
From detected waste to verified savings, every optimization stays controlled.
Identify infrastructure waste and inefficient AI usage.
Estimate savings, quality, risk, and recovery options.
Apply budget and execution policies before changes run.
Run authorized optimizations through scoped identities.
Verify
Measure savings, quality, and operational impact.
Evaluate task complexity, quality requirements, latency, data boundaries, and cost before selecting a model. Use the most cost-effective model that meets the task’s quality, latency, security, and policy requirements.
Simple classification
Route to a smaller, lower-cost model.
Complex remediation plan
Route to a higher-capability reasoning model.
Sensitive operational data
Use an approved private or customer-hosted model.
Repeated context
Reuse cached context where supported.
Token budget exceeded
Summarize, truncate, reroute, or request approval.
Agent loop detected
Pause execution and require review.
Cloud + AI
Unified cost control
Govern infrastructure actions, model selection, and token budgets through one policy layer.
One execution layer
Connect cloud and AI cost optimization with the operational capabilities your team needs. Every action follows the same controls and audit trail.