How do I deploy Flowise — LLM Agent & RAG Builder on Railway?

You can deploy Flowise — LLM Agent & RAG Builder on Railway by clicking the "Deploy Now" button on this page. Railway will automatically set up all the necessary services and configurations for you.

What are the system requirements?

Railway handles all the infrastructure requirements. You only need a web browser to deploy and manage your application.

Is this template free to use?

Yes, this template is free to use within your existing Railway account.

Can I customize this template?

Yes, you can fully customize this template. After deployment, you will have full control of what you've deployed in your Railway project.

How do I get support for this template?

You can get support through our community forum: flowise-llm-agent-rag-builder-87a873be, or click "Get template help" for this template for more assistance.

Deploy and Host Flowise — LLM Agent & RAG Builder on Railway

Flowise is an open-source drag-and-drop UI for building LLM-powered agents, RAG pipelines, and AI workflows — no coding required. Connect OpenAI, Anthropic, Ollama, and 100+ integrations visually. A self-hosted alternative to Zapier AI and Stack AI, saving teams $50–200/month.

About Hosting Flowise — LLM Agent & RAG Builder

Flowise runs as a single container with embedded SQLite — no external database required. This Railway template provisions everything automatically with a persistent volume at /root/.flowise that stores all flows, credentials, API keys, and uploads across restarts and redeployments. For larger teams, PostgreSQL and Redis can be added. Railway charges ~$5–10/month flat based on compute — no per-run fees, no operation limits, no per-seat pricing.

Platform	Flowise on Railway	Competitor
Zapier AI	~$5–10/month, no run limits	$19–69/month + per-task charges
Make.com	~$5–10/month, unlimited ops	$9–29/month with strict caps
Stack AI	~$5–10/month, open-source	$49–199/month, closed SaaS
Relevance AI	~$5–10/month, any LLM	$19–199/month

Common Use Cases

Building RAG chatbots over your own documents, PDFs, or databases
Automating internal workflows with LLM agents — research, summarization, email triage
Creating no-code AI API endpoints to power SaaS products or internal tools
Prototyping LLM chains before handing off to engineering
Running local AI workflows with Ollama — no OpenAI costs, full privacy

Dependencies for Flowise — LLM Agent & RAG Builder Hosting

Docker — runs the official flowiseai/flowise image
Persistent Volume — Railway volume at /root/.flowise stores all data

Deployment Dependencies

Implementation Details

Key environment variables: PORT=3000, DATABASE_PATH=/root/.flowise, FLOWISE_USERNAME, FLOWISE_PASSWORD. All paths are pre-configured to the persistent volume. NUMBER_OF_PROXIES=1 ensures correct IP handling behind Railway's reverse proxy.

Why Deploy Flowise — LLM Agent & RAG Builder 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 Flowise — LLM Agent & RAG Builder 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.