Deploy and Host Flowise on Railway

Flowise is your visual playground for building AI agents and workflows without writing code—just drag, drop, and connect your LLMs. Build chatbots that pull from your documents, chain AI calls together, or create custom workflows that talk to APIs. This template packages all that directly on Railway's infrastructure in one click.

Railway handles all the operational complexity—containerization, networking, SSL, scaling, uptime—so you can focus on building. No Docker knowledge needed. Click deploy and you're live in minutes with a working URL ready to go.

About Hosting Flowise

Hosting Flowise on Railway is genuinely straightforward—probably the simplest way to get Flowise running in production. There are really only two variables you need to care about: your username and password. And here's the best part—they're already pre-configured for you. If you want to change them later, it takes literally 30 seconds. Just hop into the Variables section of your Flowise node in the Railway dashboard, update whatever you want, and you're done.

This is truly one-click setup territory. You're not managing servers, databases, or complicated configurations. Railway handles all the operational heavy lifting while you focus on actually building your AI workflows. Deploy once, access it anywhere, modify settings whenever you need to. That's the whole philosophy here—get out of your own way and start creating.

Dependencies for Flowise

Flowise runs on Node.js and requires version 18.15.0 or higher to function properly. That's really it on the technical side—no complex dependency chains or compatibility headaches. The beauty of this Railway template is that all dependencies are pre-configured and bundled for you automatically.

Deployment Dependencies for Flowise

When deploying on Railway, you only need two things: a Railway account (free to create) and a valid email address for your Flowise login. That's genuinely all there is. No API keys to configure beforehand, no database setup, no environment variables to wrestle with. The template handles everything else behind the scenes—just click deploy and Railway spins up your instance with all dependencies pre-installed and ready to go.

Common Use Cases

AI Customer Support Bots
Build custom AI chatbots trained on company docs, websites, or FAQs to automate customer queries 24/7.
Document Intelligence & Q&A Upload company documents, PDFs, manuals, or training materials into Flowise and create an AI assistant that answers questions based on that specific knowledge base. Perfect for internal teams who need instant answers without digging through Google Drive or wikis.
*Lead Qualification & Sales Workflows Create conversational flows that qualify leads, gather information, and route prospects to the right sales person. Imagine a chatbot that actually understands context and asks smart follow-up questions instead of just collecting form fields.

Comparison with Other Tools

Flowise vs LangFlow

Flowise offers a more lightweight and straightforward interface — ideal for quick prototyping and low-code deployment. LangFlow, in contrast, is heavier and suited for more complex multi-node pipelines.

Flowise vs Chatbot UI

Chatbot UI focuses on frontend chat experiences, while Flowise is a backend-builder for logic and integrations. Combine both for the perfect AI app stack.

How to Use Flowise on Railway

Getting started is ridiculously easy. Click the Deploy Now button and Railway handles the rest. Deployment takes under a minute—seriously. Once it's live, you'll get a URL that's ready to go.

Click that URL and you're in. You'll see a login screen asking for an email, username, and password setup. Fill those in (remember, username and password are pre-configured, but you can customize them right now). Hit save, and you're officially in the Flowise editor.

Now you're ready to actually build. Create flows by dragging components onto the canvas—LLM models, memory modules, data loaders, API connectors. Link them together however your application needs them connected. Test on the fly. Deploy individual flows and get access URLs to integrate them wherever you need them. It's genuinely that straightforward.

How to Self-Host Flowise

Not everyone wants to use a cloud platform, and that's totally fair. Hosting Flowise yourself gives you full control and keeps everything on your own infrastructure.

Direct Route (Local or Your Own Server)

First, make sure you have NodeJS version 18.15.0 or higher installed. If you don't have it, grab it from nodejs.org.

Next, install Flowise globally using npm:

npm install -g flowise

Then start it up:

npx flowise start

If you want to set a username and password right from the start, use:

npx flowise start --FLOWISE_USERNAME=user --FLOWISE_PASSWORD=1234

Once it's running, open your browser and head to http://localhost:3000. You're in.

Flowise Cloud

Prefer a managed solution? Flowise also offers a Cloud service that’s perfect if you don’t want to deal with hosting at all.

If you want managed hosting directly from the Flowise team, they offer cloud plans:

Free Plan – $0/month, includes 2 flows and 100 predictions per month. Perfect for experimenting and prototyping.
Starter Plan – $35/month, unlimited flows and 10,000 predictions per month. Designed for individual builders and small projects.
Pro Plan – $65/month, up to 50,000 predictions per month, more storage, unlimited workspaces, and user management features. Built for teams and businesses scaling up.

Choose based on your actual needs—not everyone needs Pro, and that's okay. Start with Free or Starter and upgrade when you hit the limits.

FAQ

Q. What is Flowise?
Flowise is an open-source low-code platform that lets you visually build and deploy LLM-powered workflows and AI agents using an intuitive drag-and-drop editor.

Q. Is Flowise free to use?
Yes, Flowise is completely free for self-hosting. You only pay for hosting services like Railway or upgrade to Flowise Cloud for managed deployment.

Q: What LLMs can I connect to Flowise? Tons. OpenAI, Claude, Cohere, HuggingFace models, and many others. You configure which ones you want to use by adding API keys in your Flowise settings.

Q. How is Flowise different from LangChain?
LangChain is a developer library requiring code. Flowise builds on top of it, providing a visual UI to design and test workflows without coding.

Q. Can I integrate Flowise with my app or API?
Absolutely. You can expose your Flowise workflows as REST APIs or connect them with CRMs, websites, chatbots, or other external tools.

Q: Is this secure? Should I worry about my data? Flowise runs on Railway's infrastructure with SSL encryption and proper security practices. That said, treat your login credentials like you'd treat any password-protected service. Use strong passwords, don't share them, and keep your instance updated.

Q: Can I have multiple flows running at the same time? Yes. One Flowise instance can handle multiple flows simultaneously. You can build dozens of different workflows and deploy them all whenever you need them.

Q: Can I change the username and password after deployment? Absolutely. Go into the Variables section of your Flowise node in Railway and update them whenever you want. Changes take effect immediately.

Why Deploy Flowise | Build AI Agents, Visually 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 | Build AI Agents, Visually 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.