Cost Control & Budgeting Advanced

LLM costs can escalate rapidly without proper controls. Enterprise cost management requires budget enforcement, usage tracking by team and project, alerting, and continuous optimization to control spend while maintaining quality.

Budget Management

• Set budgets at multiple levels: organization-wide monthly budget, per-team budgets, per-project budgets, and per-API-key limits.
• Configure budget enforcement actions: warn at 80%, throttle at 90%, block at 100% with emergency override capability.
• Implement soft and hard limits. Soft limits generate alerts; hard limits actually block requests.

Cost Tracking & Allocation

• Track costs per request with accurate token counting for both input and output. Map costs to the correct provider pricing.
• Implement cost tagging: require all requests to include team, project, and use-case metadata for accurate allocation.
• Generate monthly chargeback reports showing cost breakdown by team, model, and use case for internal billing.

Cost Optimization

• Route simple tasks to cheaper models. A classification task does not need GPT-4 when GPT-3.5 produces the same result.
• Implement prompt caching to avoid re-processing identical or similar prompts. Cache hits save 100% of inference cost.
• Optimize prompt length: shorter, more focused prompts reduce input token costs without sacrificing quality.
• Use batch API endpoints for non-urgent workloads at 50% cost reduction with most providers.

Usage Analytics

• Build dashboards showing: daily/weekly/monthly spend trends, cost per team, popular models, average tokens per request.
• Identify cost outliers: unusually expensive requests, teams exceeding benchmarks, or inefficient prompt patterns.
• Forecast future costs based on usage trends and planned projects to inform budget planning.