---
title: "Deploy Langflow"
description: "Low-code app builder for RAG and multi-agent AI applications."
category: "AI/ML"
url: https://railway.com/deploy/langflow-ai
---

# Deploy Langflow

Low-code app builder for RAG and multi-agent AI applications.

**[Deploy Langflow on Railway](https://railway.com/template/langflow-ai)**

- **Creator:** codestorm
- **Category:** AI/ML

## Template content

### langflow https://djeqr6to3dedg.cloudfront.net/repo-logos/langflowai/langflow/live/logo-1731577932041.png

- **Image:** langflowai/langflow:latest
- **Public domain:** Yes

### Postgres https://devicons.railway.app/i/postgresql.svg

- **Image:** ghcr.io/railwayapp-templates/postgres-ssl:18

### Redis https://cdn.sanity.io/images/sy1jschh/production/0ce0bfdcfbdbf69662b1116671f97c2dd788b655-157x157.svg

- **Image:** redis:8.2.1
- **Start command:** `/bin/sh -c "rm -rf $RAILWAY_VOLUME_MOUNT_PATH/lost+found/ && exec docker-entrypoint.sh redis-server --requirepass $REDIS_PASSWORD --save 60 1 --dir $RAILWAY_VOLUME_MOUNT_PATH"`

## Documentation

# Deploy and Host Langflow on Railway

Langflow is a low-code visual platform for building RAG and multi-agent AI applications. It provides a drag-and-drop interface to connect LLMs, tools, memory, and APIs into production-ready workflows.

![Langflow](https://opengraph.githubassets.com/4a3fa291732195ae8467266dd5a49902a29d66a2efa92dcdd854c9c7a7e035f3/langflow-ai/langflow)

## About Hosting Langflow on Railway

This template deploys a complete Langflow stack on Railway with managed PostgreSQL for persistent data storage and Redis for job queuing. It comes pre-configured with 4 workers for better performance under load. Auto-login is enabled by default for quick start, while still allowing you to enable proper authentication easily later. Railway automatically handles HTTPS, scaling, logging, and infrastructure management.

## Key Features of This Template
- Pre-configured with **4 workers** for parallel processing
- Includes **PostgreSQL** for reliable data persistence
- Includes **Redis** as job queue for multi-worker support
- **Auto-login enabled** by default (no authentication required to start)
- Easy to enable authentication later via environment variables
- Production-ready configuration with horizontal scaling support
- Automatic HTTPS and monitoring provided by Railway

## Comparison with Alternatives

| Feature                              | This Template (Railway)      | Manual Self-Hosting | Flowise          | Dify             |
|--------------------------------------|------------------------------|---------------------|------------------|------------------|
| One-click deployment                 | ✅ Yes                       | ❌ No               | ✅ Yes           | ✅ Yes           |
| Managed PostgreSQL included          | ✅ Yes                       | ❌ Manual setup     | ❌ No            | ✅ Yes           |
| Redis + Multi-worker support         | ✅ Pre-configured (4 workers)| ❌ Complex          | ❌ Limited       | ✅ Yes           |
| Auto-login ready out of the box      | ✅ Yes                       | ❌ Manual config    | ✅ Yes           | ✅ Yes           |
| Easy to enable auth later            | ✅ Simple env change         | ❌ Complex          | ✅ Yes           | ✅ Yes           |
| Automatic HTTPS & Scaling            | ✅ Fully managed by Railway  | ❌ Manual           | ✅ Yes           | ✅ Yes           |
| Infrastructure maintenance           | ✅ Handled by Railway        | ❌ Self-managed     | ✅ Yes           | ✅ Yes           |
| Best for quick prototyping           | ✅ Excellent                 | ❌ Slow             | ✅ Good          | ✅ Good          |
| Best for production workloads        | ✅ Strong (with workers)     | ❌ High effort      | ⚠️ Limited       | ✅ Good          |

## Common Use Cases
- Building and testing RAG pipelines visually
- Developing multi-agent AI systems and workflows
- Creating internal AI tools, assistants, and automation
- Rapid prototyping of LLM-powered applications
- Running production AI workflows with better performance using multi-worker setup

## Dependencies for Langflow Hosting
- PostgreSQL (for persistent storage of flows, components, and user data)
- Redis (for job queue when using multiple workers)

### Deployment Dependencies
- Official Langflow Docker image (`langflowai/langflow:latest`)
- Railway PostgreSQL service
- Redis service

### Implementation Details
This template is optimized for both development and production use:

- **Multi-worker**: Pre-set to 4 workers with Redis queue
- **Auto-login**: Enabled by default (`LANGFLOW_AUTO_LOGIN=true`)
- **Database**: Uses managed PostgreSQL instead of SQLite
- **Enabling Auth**: Change `LANGFLOW_AUTO_LOGIN` to `false` and set `LANGFLOW_SUPERUSER` + `LANGFLOW_SUPERUSER_PASSWORD`, then redeploy

## Why Deploy Langflow on Railway?
Railway is a singular platform to deploy your infrastructure stack. Railway will host your infrastructure so you don't have to deal with configuration, while allowing you to vertically and horizontally scale it.
By deploying Langflow on Railway, you are one step closer to supporting a complete full-stack application with minimal burden. Host your servers, databases, AI agents, and more on Railway.

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Open this page in a browser: https://railway.com/deploy/langflow-ai