Fintech company Ramp has launched its own AI model router, a service designed to simplify how businesses access and switch between large language models (LLMs). The new offering, simply called Router, is available via an API and is the result of three years of internal development and usage at the company. This move positions Ramp alongside other fintech giants like Stripe in building infrastructure for the rapidly growing AI inference economy.
Ramp’s AI Model Router Goes Live
Ramp’s foray into AI infrastructure marks a significant expansion beyond its core corporate expense management platform. The AI model router is designed to give users and companies a flexible way to manage their AI usage without being locked into a single provider. By offering this service, Ramp is addressing a critical pain point for developers and enterprises alike: the need to efficiently navigate an increasingly fragmented landscape of large language models.
The Router provides access to a variety of prominent AI models, including offerings from:
OpenAI
Anthropic
DeepSeek
Moonshot
Minimax
Nvidia
xAI
This selection allows developers and businesses to experiment with and deploy different models through a single, unified API, streamlining the development process for AI-powered applications. Rather than integrating with each model provider individually, users can connect once to Ramp’s AI model router and gain immediate access to a growing ecosystem of LLMs.
How the AI Model Router Works
The core functionality of the AI model router lies in its “strategies,” which enable users to route AI requests to models based on specific preferences and benchmarks. This allows for greater control over performance, cost, and reliability, making the service suitable for both experimental projects and production-grade applications.
For example, users can set a preference for a model provider’s flexible usage tiers, which can help reduce costs during periods of lower demand. Alternatively, they can let Router choose which model to route queries to based on up to three user-specified benchmarks, such as accuracy, speed, or cost-efficiency. This ensures that the most appropriate model is used for each task, whether it involves simple text generation or complex reasoning problems.
The AI model router also enables more sophisticated routing strategies. Users can choose to route only the most difficult problems to more expensive, high-performance models while sending routine queries to more cost-effective options. Additionally, the service makes it easy to test new models without having to reconfigure their entire system, reducing friction and accelerating innovation.
Features, Dashboard, and Data Policy
To provide transparency and control, Router comes with a comprehensive dashboard. This interface lets users monitor key metrics, including:
Token spend
Cost
Latency
Fallback attempts
Model performance trends
This visibility is crucial for businesses looking to optimize their AI budgets and performance. With detailed analytics at their fingertips, engineering and finance teams can make data-driven decisions about which models to use for which tasks, ultimately improving both efficiency and ROI.
On the data privacy front, Router has an opt-out data retention policy. By default, the service will record model inputs, outputs, and tool calls for one year. However, Ramp has stated that it will remove personally identifiable information (PII) before using any data to improve the product. This approach balances the need for continuous improvement with a commitment to user privacy, giving customers the option to opt out if they have stricter data handling requirements.
Ramp’s Strategic Move into AI Infrastructure
For Ramp, which is already known for its corporate expense management platform and AI token usage monitoring, entering the model routing business makes strategic sense. The launch of its AI model router allows the company to tap into the rapidly expanding AI inference market while also offering its existing clients a new and complementary service.
By providing a robust model routing service, Ramp can build long-standing relationships with AI labs and inference providers globally. This could serve as a powerful acquisition channel, helping the company gain new customers and create new entry points for selling its broader expense management products. This move comes on the heels of Ramp’s significant growth, having raised $750 million at a $44 billion valuation in June, giving it substantial resources to invest in this new venture.
Furthermore, the AI model router functions similarly to how OpenRouter operates, though the latter currently offers more model options. However, Ramp’s deep existing relationships with enterprise clients and its expertise in expense management give it a unique competitive advantage. The company is well-positioned to offer a more integrated experience, combining AI routing with cost monitoring and financial controls that its customers already rely on.
Free Service and Launch Offer
Currently, the AI model router is available exclusively in the United States. To encourage adoption, Ramp is offering the service for free for the remainder of 2026, although users will still be responsible for the inference costs of the underlying AI models. Additionally, the company is sweetening the deal with a $26 credit launch offer, providing even more incentive for developers to try the platform.
While Ramp has not yet announced pricing for the service in 2027, the current offer provides a low-risk opportunity for developers to explore the platform, integrate it into their workflows, and evaluate its performance. For early adopters, this is an ideal time to experiment with the AI model router and determine whether it fits their AI development needs.
The Future of AI Model Routing
As the AI landscape continues to evolve, tools like Ramp’s AI model router will become increasingly essential. With new models being released at a rapid pace, businesses need flexible infrastructure that allows them to adapt quickly without overhauling their entire stack. Ramp’s entry into this space validates the growing importance of model routing and inference management in the enterprise AI ecosystem.
For developers and companies looking to simplify their AI operations, Ramp’s AI model router represents a compelling new option. Its combination of flexible routing strategies, transparent pricing, and integration with Ramp’s broader financial tools makes it a service worth exploring. Whether you are building AI-powered applications or managing enterprise AI spend, this new offering from Ramp deserves attention.
