** 📝 Notes: ** Use the Flowise AI with Workers template (https://railway.com/deploy/flowiseai-with-workers?referralCode=KKAfTD) if you need to run Flowise using a Queue for high-throughput and parallel processing.

Deploy Flowise with Railway (Upgraded to Flowise 3)

✨ Features

• Pre-configured persisted volume.
• Most of the Flowise configs are pre-configured.
• Use PostGIS as the default database for Flowise.
• The communication from Flowise to the database is accomplished through the Railway internal private network, reducing unnecessary egress fees.

✅ Prerequisite

• Postgres or PostGIS is deployed to an environment on Railway
• Flowise and PostGIS have to be deployed to the same environment to leverage the benefits of private networking on Railway.
• flowise database is created in PostGIS

💁‍♂️ Usage

🚀 Quick start

1. Click Deploy Now

2. Change to your preferred repository name

3. Click Configure and click Save Config for both services.

4. Click Deploy.

5. Let Railway deploy all the services for you.

6. Once the process is successful, you will be able to view a deployed URL.

💡 What if I would like to use my current Postgres/PostGIS database server?

1. Click Deploy Now

2. Change to your preferred repository name

3. (Important) Configure the database-related environment variables to point to your current PostGIS database.

• DATABASE_HOST (Private or public network database host. i.e. postgre.railway.internal)

• DATABASE_NAME (Database name. i.e. flowise)

• DATABASE_PASSWORD (Database user password)

• DATABASE_PORT (Database private or public network port. i.e. 5432)

• DATABASE_USER (Database user - A database user that allows you CRUD the flowise database)

4. Click Deploy

5. Let Railway deploy all the services for you.

6. Once the process is successful, you will be able to view a deployed URL.

7. Delete the PostGIS database service that comes with this template if no longer needed.

💁‍♀️ Example screenshots

Deploy and Host FlowiseAI on Railway

FlowiseAI is a low-code/no-code platform for building customized LLM orchestration flows and AI agents. It provides a drag-and-drop interface to create conversational AI applications, chatbots, and complex AI workflows without extensive coding knowledge, making AI development accessible to both developers and non-technical users.

About Hosting FlowiseAI

Hosting FlowiseAI involves deploying a Node.js application that requires a persistent database for storing chat flows, configurations, and conversation histories. The deployment needs proper environment configuration for database connections, authentication settings, and storage volumes for maintaining data persistence. This template simplifies the process by providing pre-configured settings, automatic database setup with PostGIS, and optimized internal networking to reduce costs while ensuring reliable performance and scalability.

Common Use Cases

• Building customer support chatbots with custom knowledge bases and automated response flows
• Creating AI-powered content generation workflows for marketing teams and content creators
• Developing conversational AI assistants for internal business processes and employee onboarding
• Prototyping and testing LLM applications before moving to production environments

Dependencies for FlowiseAI Hosting

• PostgreSQL or PostGIS database for data persistence and chat history storage
• Node.js runtime environment with sufficient memory allocation for LLM processing

Deployment Dependencies

• Flowise AI with Workers template - Use this alternative if you need high-throughput processing with queue-based parallel execution
• Original Railway template inspiration - Reference implementation for basic Flowise deployment

Implementation Details

This template includes several pre-configured optimizations:

# Key environment variables automatically configured:
DATABASE_HOST: postgre.railway.internal  # Internal networking
DATABASE_NAME: flowise
DATABASE_PORT: 5432
FLOWISE_USERNAME: admin  # Default admin credentials
FLOWISE_PASSWORD: 1234   # Change after deployment

The deployment uses Railway's internal private networking to connect Flowise to PostGIS, eliminating external database connection fees. A persistent volume is automatically mounted to ensure chat flows and configurations survive service restarts.

Why Deploy FlowiseAI 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 FlowiseAI 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.

Credit

• Inspired from https://railway.app/template/pn4G8S, https://github.com/FlowiseAI/Flowise/tree/main/docker and https://github.com/HenryHengZJ/FlowiseAI-Railway/blob/main/Dockerfile