Ramp has launched Router, a platform for routing AI requests between multiple large language models through a single application programming interface. The company says it developed and used the router internally to meet its AI-related needs over the past three years before making it available to users and companies.
The move comes as technology companies increasingly build intermediary layers to manage access to AI models and the costs of using them. Router works similarly to OpenRouter, but it starts with fewer models and available options than that service.
Multiple Models and Strategies Through a Single Interface
Router provides access to models from OpenAI, Anthropic, DeepSeek, Moonshot, Minimax, Nvidia, xAI, and Z.ai. Instead of connecting applications to a single model, users can choose how to route requests according to a set of strategies provided by the service.
These options include preferring flexible usage tiers from model providers, or allowing Router to determine the most suitable model for each request based on up to three performance criteria specified by the user. Requests can also be directed to more expensive models only when they are difficult, or different models can be tested without changing the software integration each time.
The service includes a dashboard displaying data such as token spending volume, cost, response time, attempts to switch to alternative models, and other details related to request usage.
What Changes for Companies in Practice?
Router combines model access management with monitoring of token consumption and costs. This may allow companies to balance answer quality against inference costs, rather than dealing with each model provider or application separately. The service also aligns with Ramp’s existing products for monitoring AI token usage and managing related spending.
For teams testing multiple models, a unified interface could be a way to reduce operational complexity. However, the actual benefit will depend on the number of supported models, the accuracy of the routing mechanisms, and the level of control the platform provides in production environments.
Availability, Data, and Cost
The service is currently available only in the United States. It will be free through the end of 2026, while users will continue to bear the inference costs associated with AI models. Ramp also announced a $26 launch credit, but it has not yet specified the service’s price after 2026.
Router follows a data-retention policy that allows retention to be disabled, although the default setting provides for recording model inputs, outputs, and tool calls for one year. The company says it will remove personally identifiable information before using this content to improve the product. The details of how the retention opt-out is implemented remain an important consideration for organizations handling sensitive data.
Ramp’s Bet on the Inference Market
The launch of Router is not limited to adding a new tool to Ramp’s portfolio; it gives the company an entry point into the growing inference-services market and may also help it build long-term relationships with AI labs and infrastructure providers.
If Router becomes an attractive platform for testing models, as OpenRouter has, Ramp could use these relationships to reach new customers and later connect them with its expense-management products. The company raised $750 million in June at a valuation of $44 billion, according to the source article.