Comparisons

A common question is: "How is Cencori different from X?"

The short answer: Cencori is the Infrastructure Layer. We are not just a model router, and we are not just a JS library. We are the cloud platform that powers your AI application.

OpenRouter is a pipe. Cencori is a platform.

Summary: Use OpenRouter if you just need access to a specific model. Use Cencori if you are building a production application that needs security, reliability, and billing.

LangChain is a library you have to host. Cencori is a serverless backend.

Summary: You can actually use LangChain with Cencori. Use LangChain for the graph logic, and let Cencori handle the LLM execution, security scanning, and billing/observability.

Vercel AI SDK is the Frontend. Cencori is the Backend.

Better Together:

import { cencori } from 'cencori/vercel';
import { streamText } from 'ai';
 
// Vercel handles the Streaming & UI
const result = await streamText({
  // Cencori handles the Intelligence, Security, & Observability
  model: cencori('gpt-4o'),
  messages
});

Vercel AI Gateway focuses on caching and rate limiting. Cencori focuses on Intelligence.

Summary: Cencori is an Active intelligence layer, whereas Vercel AI Gateway is a Passive network layer.

LiteLLM is a Python library/proxy. Cencori is a managed cloud platform.

Summary: LiteLLM is great for standardizing APIs if you want to manage your own proxy. Cencori provides the same standardization but adds managed infrastructure, security, and billing.

Portkey & Helicone are primarily Observability Gateways. Cencori is an Intelligence Platform.

Summary: Portkey and Helicone tell you what happened (Logging). Cencori helps you manage and monetize what happens (Billing, Security, Observability).

Mastra is a TypeScript framework. Cencori is the infrastructure that powers it.

Summary: Mastra is like "Next.js for Agents" (the framework). Cencori is the "Vercel for Agents" (the platform). You can use them together, or let Cencori handle the backend complexity entirely.