# AI cost control — Use case > Token-aware routing, semantic caching, per-team budgets, and per-call attribution. Watch AI spend turn from a quarterly surprise into a line you control. *Executives · AI economics · For executives* ## Pay for what you use. See where it went. Apinizer's AI Gateway routes calls to the cheapest model that satisfies the SLA, caches answers semantically, enforces per-team budgets, and attributes every token to the consumer that asked for it. [Request a demo](https://calendly.com/apinizer/15min) · [Read the docs](https://apinizer.com/developers/docs) --- ## The problem *The problem* ### AI bills don't show up in the procurement cycle. They show up in the close. Engineers point a service at a frontier model. Token meters spin. The bill is fine in week one, alarming in month one, and a board-level conversation by quarter end. By then attribution is impossible — twelve teams share one API key, and nobody knows which prompt cost what. Apinizer puts every AI call through a gateway that meters, attributes, caches, and routes — before the spend happens. --- ## At a glance - **40-70%** — spend cut (semantic cache + smart routing) - **100%** — calls attributed (per team / project / consumer) - **Real-time** — budget alarms --- ## Capabilities ### Semantic caching Equivalent prompts hit cache, not the model. 'Summarize this contract' on the same contract serves from cache; the underlying model is never called twice for the same answer. ### Smart model routing Route simple intents to small / cheap models, complex intents to frontier models. The gateway picks per call, not per service. ### Per-team budgets Hard caps and soft alarms per project, team, or consumer. When a budget is reached, the gateway throttles or fails over — no surprise. ### Per-call attribution Every token tagged with consumer, project, and prompt fingerprint. Cost shows up in the dashboard the day it was spent. ### Token economics Prompt tokens, completion tokens, cache hits, fallbacks — broken out by model, endpoint, and consumer. Finance gets the same view as engineering. ### Quotas with policy Power users get more; weekend batch jobs get less. Quotas are a policy you write once and the gateway enforces on every call. --- ## Real-world examples ### Banking **Scenario:** Istanbul bank cuts AI spend 58% on customer-service summaries **Outcome:** Semantic cache absorbs 71% of duplicate prompts. Routing sends short intents to a smaller model; only escalations reach the frontier provider. **Metric:** −58% monthly ### Manufacturing **Scenario:** Stuttgart OEM caps each engineering team's monthly AI budget **Outcome:** Per-team budgets at €X. Alarms fire at 80%; throttle at 100%. The CFO sees burn rates instead of surprise invoices. ### E-commerce **Scenario:** Amsterdam marketplace attributes AI cost back to product squads **Outcome:** Every token is tagged with the squad that asked for it. Cost showbacks appear in the existing FinOps dashboard. ### Insurance **Scenario:** Paris insurer routes claim summarization to a regional model **Outcome:** EU-hosted model handles 92% of summaries; frontier provider used only for adversarial or multi-language cases. Latency improves and spend drops together. **Metric:** −42% spend, +18% latency ### Telecom **Scenario:** Madrid carrier shifts batch enrichment to off-peak smaller models **Outcome:** Time-of-day policy: night batch on the cheap tier, daytime live traffic on the premium tier. Cost-to-serve drops without an SLA change. ### Public sector **Scenario:** Prague ministry budgets AI per department in advance **Outcome:** Department quotas published. Departments see real-time burn; over-runs require a written request, not a surprise email. ### Government **Scenario:** Riyadh agency uses a national-language model for 80% of calls **Outcome:** Routing prefers the national Arabic model first; falls over to international providers only on miss. Sovereignty and cost align. ### Retail **Scenario:** Milan retailer cuts product-description AI cost 64% **Outcome:** Semantic cache deduplicates near-identical SKU prompts. Routing handles long-form on a frontier model; short-form on a 7B open model. **Metric:** −64% spend --- ## Recommended modules - [AI Gateway](https://apinizer.com/products/ai-gateway) — Token-aware routing, semantic caching, per-team budgets, prompt firewalls — the AI cost lane. - [Analytics Engine](https://apinizer.com/products/analytics-engine) — Per-team, per-consumer, per-model breakdowns — finance and engineering on the same view. - [Cache](https://apinizer.com/products/cache) — Distributed cache that backs the semantic layer with deterministic invalidation. - [Monitoring](https://apinizer.com/products/monitoring) — Alarms on budget burn rates, anomaly detection on prompt spend, severity-aware action chains. --- ## Resources - [AI economics on Apinizer](https://docs.apinizer.com/en) — Routing, caching, attribution, quotas — how the AI Gateway controls spend. - [AI Gateway](https://apinizer.com/products/ai-gateway) — The AI lane — every model call through one governed plane. - [Cache](https://apinizer.com/products/cache) — Distributed cache backing semantic responses. - [Analytics Engine](https://apinizer.com/products/analytics-engine) — Per-team, per-consumer cost dashboards. - [Token economics](https://apinizer.com/solutions/token-economics) — The engineering view of the same problem. - [Architecture overview](https://docs.apinizer.com/en/concepts/architecture) — Where the AI lane sits relative to API and identity surfaces. --- ## Related use cases - [Multi-LLM routing](https://apinizer.com/solutions/multi-llm-routing) — For AI teams - [AI Gateway](https://apinizer.com/solutions/ai-gateway) — For AI teams - [Token economics](https://apinizer.com/solutions/token-economics) — For AI teams - [AI observability](https://apinizer.com/solutions/ai-observability) — For AI teams --- ## Next step *Make AI spend a line you control* **Stop being surprised by the bill.** A 30-minute walkthrough — routing, caching, budgets, attribution — on a Kubernetes of your choice. [Book a Demo](https://calendly.com/apinizer/15min) · [Read the docs](https://apinizer.com/developers/docs) --- ## Links - Products: https://apinizer.com/products - AI Gateway: https://apinizer.com/products/ai-gateway - Solutions: https://apinizer.com/solutions - Pricing: https://apinizer.com/pricing - Developers: https://apinizer.com/developers - Documentation: https://docs.apinizer.com/index-en - Blog: https://apinizer.com/blog - Contact: https://apinizer.com/company/contact © 2026 Apinizer. All rights reserved.