One API for All Your AI Needs
For the past three years, Ramp has been using a proprietary routing layer to power its own internal AI workloads. Now the company is opening that same engine up to external customers, allowing them to direct requests to a curated selection of language models from OpenAI, Anthropic, DeepSeek, Moonshot, Minimax, Nvidia, xAI, and Z.ai.
Router’s design mirrors the concept of a toll‑booth for AI: businesses can specify routing rules based on cost tiers, latency thresholds, or performance benchmarks. For example, a user can tell Router to send only the most complex queries to the most expensive models, while cheaper alternatives handle routine tasks.
Free to Use, Cost‑Efficient to Deploy
Ramp’s pricing structure is straightforward.(serializers) Router itself is free through the end of 2026; the only fees come from the underlying model providers. To sweeten the launch, new customers receive a $26 credit that can be applied#w to any model usage.
Unlike some competitors, Router offers an opt‑out data retention policy. By default, the system logs inputs, outputs, and tool calls for up to one year. However, it automatically strips personally identifiable information before using that data for product improvements.
Dashboard and Analytics
Users gain access to a dashboard that tracks token spend, cost, latency, fallback attempts, and more. This visibility aligns with Ramp’s core product suite, which already includes AI token usage monitoring and expense management tools. The combined offering allows companies to keep a tight leash on AI spend while experimenting across multiple vendors.
Strategic Implications for Ramp
Entering the model‑routing space serves a dual purpose. First, it taps into the booming AI inference market, which is projected to grow at a compound annual rate of 30% over the next decade. Second, it deepens Ramp’s integration with its existing customer base, offering a seamless way for fintech users to manage billing, compliance, and cost efficiency in one platform.
By positioning Router as a testing ground for new LLMs, Ramp could forge lasting partnerships with AI labs and inference providers worldwide. Such relationships would not only expand its service portfolio but also create new revenue streams for its expense‑management products.
Looking Ahead
Ramp’s recent fundraising round—$750 million at a $44 billion valuation—provides the capital cushion needed to iterate on Router and expand its feature set. While the company has not yet disclosed a pricing model beyond 2026, the initial free tier and credit offer suggest a strategy focused on rapid user adoption and data‑driven product refinement.
As the AI ecosystem evolves, services like Router will become essential for businesses that require flexibility, cost control, and an aggregated view of multiple model providers. Ramp’s entry into this space signals a broader trend: fintech platforms are increasingly blurring the lines between financial tools and AI infrastructure.
