Better qualityLower costLower latency
AI inference, on autopilot.
Dynamically route inference requests to the best model in real time, based on quality, cost, and latency.
Models from the leading AI providers, ready to use.
One API call. The right
model, every time.
One OpenAI-compatible API for every model. We classify each prompt and route it to the best fit, so you never hand-pick a model per request.
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Prompt classification
The classifier detects task type (code generation, analysis, translation) and complexity from the prompt itself. Simple queries route to smaller, cost-efficient models. Complex tasks are directed to higher-capability ones.
Optimize for cost, quality, or speed
Four modes, Balanced, Best Quality, Cheapest, and Fastest, weigh each model on benchmarks, price, and latency toward the target you choose.
Transparent routing decisions
A single API call handles classification, model selection, and response streaming, with no orchestration on your side. The routing decision, the chosen model, task, and scores, streams back inline so you always know what ran and why.
Not sure which model fits?
Describe your use case.
Define your requirements and get ranked recommendations in seconds.
Try with your own use caseIndustry
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For Code Review & Bug Detection in Software & Technology at startup scale, prioritizing best quality and speed
Everything you need, from
prompt to production.
Inference, smart routing, and the tools around them, in one place.
Inference API
Run any model through one OpenAI-compatible endpoint. Smart routing picks the best fit per prompt.
Model Catalog
Hundreds of models with benchmarks, capabilities, context window, and licensing in one place.
Model Comparison
Side-by-side evaluation across capabilities, performance, context, and price.
Use Case Recommender
Describe what you are building. Get ranked model recommendations scored on fit, cost, and capability.
Capacity Planning
Estimate VRAM, GPU requirements, and cost when you plan a self-hosted deployment.
From the blog.
Benchmarks, cost analysis, and the thinking behind how we build.
Router Redesign, Clean Slate Notes (INTERNAL DRAFT)
Living document for the clean-slate router redesign. Internal use only. Do not deploy.
What Is a Context Window? How LLM Context Limits Work and Why the Headline Number Misleads
A context window is the slice of text a language model can read and generate inside a single request. This post explains how context windows actually work, why the advertised length and the usable length rarely match, and how to size a context budget for production workloads.
The Real Cost of Inference at Enterprise Scale: A 2026 Pricing Audit
A cross-provider audit of LLM inference pricing in May 2026, applying the four-factor cost framework to real numbers across frontier models, OSS hosts, and self-hosted GPUs.
Start building with the right model.
Automatically route workloads to the right model for every task, every time.