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.

vs OpenRouter

OpenRouter is a pipe. Cencori is a platform.

Feature	OpenRouter	Cencori
Model Routing	Yes	Yes (14+ Providers)
Unified API	Yes	Yes (OpenAI Compatible)
Integrations	No	Vercel, Zapier, Supabase
Security	No	PII Redaction, Prompt Injection
Memory	No	Adaptive Memory (Vector Store)
Workflows	No	Agent Orchestration

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

vs LangChain / LangGraph

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

Feature	LangChain	Cencori
Model Routing	Yes (via Adapter)	Yes (Native)
Unified API	Yes	Yes
Integrations	Yes (Code)	Yes (Native & Code)
Security	No	PII Redaction, Prompt Injection
Memory	Partial (Self-Hosted)	Adaptive Memory (Managed)
Workflows	Yes (LangGraph)	Agent Orchestration (Serverless)
Hosting	Self-hosted (e.g. EC2, Fargate)	Serverless Cloud
State	Redis/Postgres (Manual)	Built-in Persistence
Retries	You code it	Built-in (Exponential Backoff)
Observability	LangSmith (Separate)	Integrated Dashboard

Summary: You can actually use LangChain with Cencori. Use LangChain for the graph logic, and let Cencori handle the LLM execution, memory storage, and observability.

vs Vercel AI SDK

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

Feature	Vercel AI SDK	Cencori
Model Routing	Yes (Client-side)	Yes (Server-side)
Unified API	Yes	Yes
Integrations	Yes (Frontend)	Yes (Backend)
Security	No (Client-side only)	Enterprise-grade (PII, Injection)
Memory	No	Vector Store + Adaptive
Workflows	No	Agent Orchestration
Role	Frontend Library	Backend Engine
Focus	UI State & Streaming	Intelligence & Security

Better Together:

Codetext

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

vs Vercel AI Gateway

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

Feature	Vercel AI Gateway	Cencori
Model Routing	Yes	Yes
Unified API	Yes	Yes
Integrations	Limited	Vercel, Zapier, Supabase
Security	Basic (Firewall)	AI-Specific (PII, Jailbreak)
Memory	Stateless	Stateful (User Memory)
Workflows	No	Agent Orchestration
Primary Goal	Caching & Rate Limiting	Agent Orchestration
Intelligence	Passive (Network Layer)	Active (Application Layer)

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

vs LiteLLM

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

Feature	LiteLLM	Cencori
Model Routing	Yes (Python Proxy)	Yes (Global Edge)
Unified API	Yes	Yes
Integrations	No	Vercel, Zapier, Supabase
Security	Basic (API Key Mgmt)	Enterprise-grade (PII, Injection)
Memory	No	Adaptive Memory
Workflows	No	Agent Orchestration
Hosting	Self-hosted	Serverless Cloud

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 memory.

vs Portkey / Helicone

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

Feature	Portkey / Helicone	Cencori
Model Routing	Yes	Yes
Unified API	Yes	Yes
Integrations	Observability-Focused	Application-Focused
Security	Audit Logs Only	Active Redaction & Blocking
Memory	No	Adaptive Memory
Workflows	No	Agent Orchestration
Primary Goal	Logging & Analytics	Building Agents

Summary: Portkey and Helicone tell you what happened (Logging). Cencori helps you make it happen (Agents, Memory, Security).

vs Mastra

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

Feature	Mastra	Cencori
Model Routing	Yes (Local)	Yes (Cloud)
Unified API	Yes	Yes
Integrations	Yes (Code)	Yes (Native)
Security	No	PII Redaction, Prompt Injection
Memory	Local / Postgres	Managed Vector Store
Workflows	Yes (Local Execution)	Serverless Execution
Hosting	Self-hosted	Serverless Cloud
State	Postgres (Manual)	Built-in Persistence

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.

Comparisons