Rather than requiring developers to choose a model for every workload, Router evaluates requests against the performance requirements a team establishes. It then sends the request to an eligible model based on cost. Developers can use Ramp’s default routing approach or configure their own strategy.
The service also includes automatic fallback when a provider becomes unavailable. Ramp says Router applies more than 100 optimizations covering areas such as model selection, caching, compression, request timing and handling. “AI is the fastest-growing line item at most companies, and the one they can least measure,” Ramp Chief Technology Officer Rahul Sengottuvelu said. “Router puts every token in one place and sends each request to the model that delivers the right performance at the right cost.”
Ramp is positioning Router as more than a standalone model-selection layer. The service connects AI usage with the company’s existing spend-management capabilities, providing businesses with information about AI costs and where that spending originates.
The launch comes as Ramp’s own data shows a sharp increase in corporate AI spending. According to the Ramp AI Index, AI expenditures have risen 20.7 times since June 2025. Router is designed around the idea that businesses do not need to use the same model for every task, particularly when different models can meet the required performance level at different costs.
Ramp determines model suitability in part through Ramp SWE-Bench, a benchmark based on production engineering tasks from within the company. Router continually evaluates new models using that work and can incorporate models and routing methods into its default configuration when they demonstrate suitable cost and performance characteristics. The benchmark gives Ramp a way to test model selection against its own engineering workloads rather than relying exclusively on public leaderboards. The company does not claim, however, that those workloads represent every type of application businesses may send through Router.
Ramp originally developed the routing technology for internal use three years ago. The company says matching workloads with different models reduced its own inference spending by approximately 30% without changing the output while maintaining reliability above 99.9% across production traffic. “We're all about saving money, for ourselves and our customers,” Sengottuvelu said. “When something we build works well for Ramp, we want to put it in our customers' hands too.”
Anthropic is among the AI providers available through Router at launch. “Anthropic offers leading models across the cost and performance curve so developers can optimize for intelligence on hard problems or for speed and cost where that matters more,” said Katelyn Lesse, Anthropic’s head of platform engineering. “Router helps make the optimal choices with a simple integration, and Claude is available from day one.”
SpaceXAI models are also supported. “Developers should be able to use powerful AI models wherever they build,” the company said. “We're excited for Grok to be available through Ramp's new Router offering, expanding the ways teams can bring SpaceXAI models into their applications.”
Router is available now and its routing service will remain free through 2026. New users receive $26 in credits, while model tokens are charged at their listed prices.
For Ramp, the product extends its cost-management approach into AI infrastructure. Instead of treating model selection and financial oversight as separate decisions, Router combines them in one system, allowing developers to route workloads among AI providers while companies track the resulting inference spending.
This analysis is based on reporting from PR Newswire.
Image courtesy of SQ Magazine.
This article was generated with AI assistance and reviewed for accuracy and quality.
