# Multi-LLM routing — Use case > Route prompts to the right model — frontier, regional, open-weight, sovereign — by cost, latency, capability, and consent. One gateway, every provider, one audit. *AI teams · Routing · For AI teams* ## The best model for the call. Not the one wired in last quarter. Apinizer's AI Gateway routes every prompt by cost, latency, capability, and policy. Frontier model when needed; regional when sufficient; open-weight when sovereign — all under one identity, one audit, one runtime. [Request a demo](https://calendly.com/apinizer/15min) · [Read the docs](https://apinizer.com/developers/docs) --- ## The problem *The problem* ### One hard-wired model is one outage and one cost spike away from regret. Services pick a model in a sprint and inherit its bill, its rate limit, its sovereignty profile, and its outages forever. When the provider has an incident, the app does too. When a cheaper model would serve, the team pays the frontier price anyway. Apinizer turns the model into a policy decision — per call, not per service. --- ## Capabilities ### Rule-based conditional routing Route on the attributes of the call — consumer, project, headers, requested model class. Summarization to a small model, code generation to a code-specialist, vision to a multi-modal — without changing the application. ### Least-cost and least-latency routing Two routing algorithms decide for you: least-cost picks off the model catalog's unit pricing, least-latency picks off live health-probe latency. Frontier providers only when the rules say so, and a per-leg cost ceiling on every fall-back. A model past its sunset date is rejected at the gateway and dropped from the OpenAI-compatible `GET /v1/models` discovery response, so a client cannot pin itself to a model that is on its way out. ### The catalog is data, not code Twenty-six providers and 185 models ship built in, with pricing and lifecycle dates you edit in the UI. A provider that is not in the catalog — a regional vendor, an internal inference service — is defined on screen rather than through an import file, and the adapter follows the wire protocol it speaks, so a custom endpoint can talk its own native format. Adding one does not wait for a release. ### Failover and load balancing Provider hiccup? Traffic rolls to the next provider in the pool with the same capability profile. Application doesn't know there was an incident. ### Sovereignty rules you write yourself Conditional routing reads the attributes the request already carries — a header, a token claim, the consumer identity — so traffic carrying regulated data reaches only the providers you approved for that jurisdiction. The rule is data, not code, and once it is deployed it applies to every call automatically. ### Cross-family failover without client changes A fall-back leg on another vendor family gets the request rebuilt in that vendor's native format — OpenAI in, Anthropic or Gemini or Bedrock out. Retries stay idempotent, so a failed leg is never billed twice. ### Open-weight + frontier in one pool Local llama / mistral / qwen deployments live in the routing pool alongside hosted providers. The application doesn't choose; the policy does. --- ## Real-world examples ### Banking **Scenario:** Istanbul bank routes Turkish-language calls to a local model first **Outcome:** 90% of customer-service summaries handled by a TR-tuned model hosted in-country. Frontier providers used only for adversarial or English-mixed cases. **Metric:** 90% local, 10% frontier ### Manufacturing **Scenario:** Munich OEM routes engineering Q&A to a code-specialist model **Outcome:** Code generation and review go to a code-specialized model; design-doc summarization to a general model. Tail latency drops; quality goes up. ### Insurance **Scenario:** Paris insurer keeps PII calls inside EU-hosted providers **Outcome:** Routing rule reads the request headers and payload. Anything that looks like PII routes only to providers in approved jurisdictions; everything else has the full pool. ### Retail **Scenario:** Madrid retailer fails over a provider outage in seconds **Outcome:** Frontier provider returns 5xx for 14 minutes. The gateway rolls to the secondary; application keeps serving without an incident page. **Metric:** 0 user-facing impact ### Media **Scenario:** Milan publisher trials a cheaper model in a load-balanced pool **Outcome:** The new model joins the primary pool alongside the incumbent. Per-model cost, latency, and error telemetry in the Analytics Engine settle the question in a week; cutover is one policy change, and rollback is just as easy. ### Healthcare **Scenario:** Prague hospital routes clinical Q&A only to certified models **Outcome:** Compliance-approved model list maintained centrally. Routing never picks an uncertified model; auditors stop asking 'which model answered'. ### Government **Scenario:** Riyadh ministry routes Arabic content to a national model first **Outcome:** Sovereign Arabic LLM gets first call; frontier providers as fallback. Cost falls; sovereignty story tightens. ### Energy **Scenario:** Baku utility runs operations agents on open-weight models **Outcome:** Local 70B model runs SCADA agent prompts. Hosted providers reserved for non-operational use. The agent never leaves the operator network. --- ## Recommended modules - [AI Gateway](https://apinizer.com/products/ai-gateway) — Rule-based conditional routing, least-cost and least-latency algorithms, sovereignty rules, cross-family failover. - [Analytics Engine](https://apinizer.com/products/analytics-engine) — Per-model, per-project, per-consumer telemetry to compare options. - [Cache](https://apinizer.com/products/cache) — Cache layer that backs semantic responses, regardless of which model answered. - [Monitoring](https://apinizer.com/products/monitoring) — Provider health and latency probes; severity-aware alarms on degradation. --- ## Resources - [AI Gateway routing](https://docs.apinizer.com/en) — How conditional rules, cost, latency, and sovereignty compose into routing policy. - [AI Gateway](https://apinizer.com/products/ai-gateway) — The lane every AI call lives on — providers, MCP, agents. - [Analytics Engine](https://apinizer.com/products/analytics-engine) — Per-provider, per-project, per-consumer telemetry. - [Architecture overview](https://docs.apinizer.com/en/concepts/architecture) — Where the AI lane sits in the topology. - [APIops manifests](https://apinizer.com/developers/apiops) — Routing policy ships as code, reviews in Git, applies idempotently. - [AI Gateway lane](https://apinizer.com/solutions/ai-gateway) — Where routing composes with MCP governance, A2A gateway, firewalls, and cache. --- ## Related use cases - [AI cost control](https://apinizer.com/solutions/ai-cost-control) — For executives - [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 *Right model per call* **Stop hard-wiring the LLM. Start routing it.** A 30-minute walkthrough — capability routing, cost tiers, sovereignty rules — 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.