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RouterBench deploys a unified, OpenAI-compatible LLM gateway inside your own AWS account - smart routing, budgets, guardrails, and full usage tracking across 100+ model providers.
Overview
RouterBench is an enterprise LLM gateway that gives your teams a single, OpenAI-compatible endpoint for accessing 100+ AI model providers - including Amazon Bedrock, OpenAI, Anthropic, and Google Vertex AI -with automatic smart routing to the most cost-effective, capable model for every request. This engagement deploys RouterBench directly inside your own AWS account (using services such as Amazon EC2, Amazon ECS/Fargate, Amazon RDS, and Amazon ElastiCache), so your prompts, responses, and API keys never leave your network. Our team handles architecture design, deployment, configuration of virtual API keys, budgets and rate limits, SSO/RBAC integration, guardrails and PII redaction, and full observability - followed by knowledge transfer so your team can operate it independently. RouterBench includes per-team virtual keys, spend budgets and token quotas, automatic provider fallback, prompt/response caching, audit logging, and a management dashboard -replacing scattered point integrations with a single governed layer for all LLM traffic.
Highlights
- Deployed entirely inside your own AWS account - your prompts, responses, and provider API keys never leave your network.
- Smart routing across 100+ LLM providers (including Amazon Bedrock, OpenAI, and Anthropic) automatically picks the most cost-effective, capable model per request.
- Enterprise governance out of the box: virtual API keys, per-team budgets and token quotas, SSO/RBAC, audit logs, and guardrails.
Details
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Pricing
Custom pricing options
Pricing is based on your specific requirements and eligibility. To get a custom quote for your needs, request a private offer.
Legal
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Support
Vendor support
Support is provided via email at support@routerbench.com , with response times of 1 business day for standard requests and same-day response for production-impacting issues under an active engagement. Each engagement includes architecture documentation, operational runbooks, and a knowledge-transfer session so your team can operate the deployment independently. Extended/premium support plans are available on request as part of your private offer.