Ramp: AI model router as cost-control infrastructure for teams

Ramp, the corporate finance platform best known for expense management, launched a public AI model routing service on August 20, 2026. Called Router, it lets companies and developers send requests to a single API endpoint and have those requests routed to language models from OpenAI, Anthropic, DeepSeek, Moonshot, Minimax, Nvidia, xAI, and Z.ai — switching between providers based on cost preference, benchmark performance, or custom routing rules.

Ramp built the system internally over three years for its own AI usage. Router includes dashboards that track token spend, latency, and fallback attempts, and logs model inputs and outputs for one year with automatic PII removal before the data is used for product improvement. The service is available at no cost through the end of 2026 (with a $26 launch credit), currently limited to US users.

The direct competitor is OpenRouter, which launched earlier and offers a broader model catalog. Ramp’s differentiation is its existing relationship with enterprise finance teams: Router sits inside a product already managing company spend, which means AI cost data can appear alongside procurement and SaaS spend in a single view.

For product managers, the launch is notable for two reasons. First, it shows that AI model selection and cost tracking are becoming routine procurement decisions rather than infrastructure bets, similar to how teams previously chose between database vendors or CDN providers. Second, the routing architecture itself — sending identical prompts to whichever model currently meets the cost-performance threshold — points toward a product world where model identity matters less to users than the quality of the wrapper around it. Teams building AI features into products will increasingly want this kind of abstraction between their application code and whatever model actually runs underneath.

Router is US-only at launch. Ramp raised $750 million at a $44 billion valuation in June 2026.