Routes AI model requests across providers, adding failover and observability.
Product memo
AI teams use routing.run to manage multiple AI model providers through a unified API endpoint. It abstracts away volatility in model quality, pricing, and uptime, letting production teams change providers or tune fallback orders without code rework. This ensures stable integrations and predictable spend, especially with its request-based pricing model.
For who
AI teams and production teams
Solves what
Abstracts AI model provider volatility for stable integrations.
- Single endpoint for multiple providers
- Live routing control
- Provider failover and cost control
In their own words
Model routing for production
One endpoint for multiple providers, fallback chains, and live routing control. Typically used by production teams of absolute necessity.
Commercial cues
Model
usage_based
Free tier
Yes
Trial
No
Operator context
Founded
May 2026
Platform
API
Audience
Developers
Public footprint
Tech stack
Builder Strategy
- Strategy Type
- Niche Specialist
- Stage
- Pre Revenue
- Effort
- Solo Buildable
About Routing Expand
Routing.run provides AI model routing for production teams, abstracting away the inherent volatility of AI model providers. It gives teams a single API endpoint to manage multiple services, ensuring stable integrations even as model quality, pricing, or uptime fluctuates.
The platform includes provider failover, observability, and privacy-first inference, which are critical for maintaining reliable AI applications. Its request-based pricing model helps teams predict costs, a key advantage over variable token-based pricing.
This approach positions routing.run as a specialist tool for AI infrastructure.