Solutions / FinOps
FinOps
Control AI and cloud costs without slowing teams down.
Argy makes AI costs visible and actionable through quotas, intelligent routing, and observability.
Outcomes
- • Predictable AI costs
- • Multi-model optimization
- • Policy-driven control
KPIs to track
- • Cost per 1M tokens
- • Forecast vs actual delta
- • Routing savings rate
Priorities
- • Make AI and cloud costs predictable
- • Prevent overages and drift
- • Optimize without re-writing apps
Argy approach
- • Quotas and credits per tenant and team
- • Automatic routing based on budget/quality
- • Cache and observability to reduce cost
Key building blocks
- • LLM Gateway + quota service
- • Audit trail and detailed consumption
- • Alerting and policy limits
Governance & sovereignty
- • Alerts and plan limits
- • Cost tracking per product/team
- • Vendor independence via routing
Direct answers
Can Argy reduce cloud spend?
Yes—by standardizing environments and governing AI costs via quotas, routing, and cache.
Related use cases
Explore concrete scenarios aligned with this solution.
Governing enterprise AI
Argy becomes the governance layer between teams and models: one entry point, shared rules, and predictable costs.
Steering execution (SLOs, observability, FinOps)
Argy standardizes run practices: observability, routines, and improvement loops are packaged and tracked.
Next step: request a demo or view pricing.