AI cost management in production

LLM APIs charge per token. A single misconfigured integration can generate thousands of dollars in a day. Cost management is not optional for production AI.

Set quotas per environment and per team. Dev and staging should have tight limits; production needs guardrails that prevent runaway usage. Use cloud billing alerts and custom dashboards to catch spikes early.

Cache aggressively. Many queries are repetitive—FAQ answers, common document lookups, similar prompts. Cache responses (with appropriate TTL and invalidation) to cut API calls and cost.

Route intelligently. Use small, fast models for classification and routing; reserve larger models for complex tasks. Tiered routing can cut cost by 50–70% without sacrificing quality for most requests.

Monitor cost per use case. Break down spend by feature, team, or endpoint. Without visibility, you cannot optimize. We help teams implement cost tracking, quotas, and optimization strategies so AI remains cost-effective at scale.