Deploy Flowise — AI Agent Builder

Deploy and Host Flowise - AI Agent Builder on Railway

Flowise is an open-source visual platform for building AI agents, LLM workflows, chat applications, and multi-agent systems. It provides a drag-and-drop interface for connecting models, tools, APIs, vector databases, memory, custom code, and workflow logic without building every integration from scratch.

About Hosting Flowise

This template deploys Flowise with PostgreSQL and persistent storage, providing a practical foundation for building and running AI workflows.

Flowise provides several ways to build AI applications, including Chatflows, Assistants, and Agentflows. Agentflow supports conversational assistants, single-agent systems, multi-agent architectures, and more complex workflow orchestration.

PostgreSQL stores Flowise application data, while persistent storage preserves local Flowise files such as secrets, API keys, logs, and uploaded data across restarts and redeployments.

Included Architecture

                    ┌─────────────────┐
                    │      User       │
                    └────────┬────────┘
                             │
                             ▼
                  Railway HTTPS Proxy
                             │
                             ▼
                    ┌─────────────────┐
                    │     Flowise     │
                    │                 │
                    │ Agentflows      │
                    │ Chatflows       │
                    │ AI Tools        │
                    └────────┬────────┘
                             │
                    Private Network
                             │
                             ▼
                    ┌─────────────────┐
                    │   PostgreSQL    │
                    │                 │
                    │ Persistent DB   │
                    └─────────────────┘

Common Use Cases

• Build AI agents visually
• Create LLM-powered chat applications
• Build multi-agent systems
• Connect models from multiple AI providers
• Build RAG and knowledge-based applications
• Connect vector databases and memory systems
• Call APIs and external tools from AI workflows
• Add branching, looping, and routing logic
• Build internal AI assistants
• Create reusable AI workflows
• Expose AI applications through APIs
• Embed AI chat interfaces into websites

Flowise also provides a Prediction API for interacting with deployed flows and supports streaming responses for real-time chat experiences.

Flowise vs Other AI Workflow Platforms

Flowise is especially useful when you want visual AI orchestration while still retaining access to custom code, APIs, tools, models, and advanced workflow logic.

Flowise Capabilities

Flowise supports:

• Agentflow
• Chatflow
• AI assistants
• Single-agent systems
• Multi-agent systems
• Custom code
• Branching and routing
• Loops and workflow logic
• API integrations
• Vector databases
• Memory
• Document stores
• Tools
• Open-source and proprietary AI models
• Embedded chat widgets

Flowise's Document Stores can also be used to upload, split, prepare, and upsert datasets for retrieval-based AI applications.

Persistent Storage

This template uses persistent storage for both Flowise and PostgreSQL.

Persistent Flowise data can include:

• API keys
• Secret keys
• Uploaded files
• Blob storage
• Logs
• Application-related local files

PostgreSQL stores the main Flowise application database.

This means important application state survives service restarts and redeployments.

Health Check

The template includes a health check using:

/api/v1/ping

Flowise's official Docker Compose configuration uses this endpoint to verify that the application is running and responding correctly.

This allows Railway to detect unhealthy deployments and better manage service availability.

Getting Started

After deployment:

1. Open the public Railway domain assigned to the Flowise service.
2. Open the Variables tab in the Flowise service.
3. Copy the values of:

FLOWISE_USERNAME
FLOWISE_PASSWORD

4. Return to the Flowise page.
5. Log in using those credentials.
6. Create your first Chatflow or Agentflow.
7. Add an AI model provider.
8. Connect tools, APIs, memory, or vector databases as needed.
9. Test the flow.
10. Deploy or expose it through Flowise's available interfaces and APIs.

Building AI Agents

For more advanced applications, use Agentflow.

Agentflow can be used for:

• Conversational assistants
• Single-agent workflows
• Multi-agent systems
• Tool-calling agents
• Conditional routing
• Sequential execution
• Complex workflow orchestration

Flowise documents Agentflow V2 as its current architecture for building multi-agent and advanced agent workflows.

API and Integration

Flowise flows can be called programmatically through the Prediction API.

This makes Flowise useful as an AI backend for:

• Web applications
• Mobile apps
• n8n workflows
• Internal systems
• Chat interfaces
• AI agents
• Automation platforms
• API services

Flowise also supports embedding chat widgets directly into websites.

Security Note

Flows may be accessible through their Flow ID depending on how they are configured.

For flows that should not be publicly callable, Flowise supports assigning API keys at the flow level.

Always configure access control appropriately before exposing production AI workflows publicly.

Dependencies for Flowise Hosting

• Flowise — visual AI agent and workflow platform
• PostgreSQL — persistent application database
• Persistent Volume — stores Flowise application files
• Railway Private Networking — internal communication with PostgreSQL
• Railway Public Networking — HTTPS access to Flowise
• Health Check — application monitoring via /api/v1/ping

Deployment Dependencies

• Flowise Documentation: https://docs.flowiseai.com/
• Flowise GitHub: https://github.com/FlowiseAI/Flowise
• Agentflow V2: https://docs.flowiseai.com/using-flowise/agentflowv2
• Flowise Prediction API: https://docs.flowiseai.com/api-reference/prediction
• Flowise Embed: https://docs.flowiseai.com/using-flowise/embed

Why Deploy Flowise - AI Agent 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 - AI Agent Builder on Railway, you get a visual AI development platform with persistent storage, PostgreSQL, built-in health monitoring, private networking, and a simple path from agent prototype to deployed AI workflow.