Flowise

What is Flowise?

Flowise is an open-source generative AI development platform enabling visual construction of AI agents, chatbots, and complex LLM workflows using LangChainJS as core orchestrator. Unlike conventional automation tools, Flowise specializes in orchestrating advanced agentic systems through intuitive drag-and-drop interfaces, supporting both single-agent and multi-agent workflows without extensive coding.

Licensed under Apache 2.0, Flowise provides unrestricted self-hosting capabilities with community-driven enhancements. The platform offers three distinct visual builders: Assistant (form-based for rapid chatbot creation), Chatflow (node-based for flexible single-agent LLM flows), and Agentflow (advanced multi-agent orchestration with branching, looping, and state management).

Deep integration with LangChainJS provides powerful tools for memory management, retrieval-augmented generation (RAG), embeddings, and complex agent behaviors. Flowise supports over 100 LLM models, integrates with major vector databases, and enables deployment through REST APIs, SDKs, or embeddable chat widgets.

Core Features

Visual Workflow Builder
Modular, node-based canvas for building LLM-powered workflows through drag-and-drop node connections.

• Connect nodes representing LLMs, retrievers, databases, memory, logic
• Reusable templates and community-contributed flows
• Assistant, Chatflow, Agentflow builder options
• Real-time flow validation and testing

Multi-Agent Orchestration
Agentflow supports sophisticated multi-agent system design.

• Explicit workflow orchestration with discrete node operations
• Agent-to-agent communication with shared conversation history
• Supervisor agents delegate tasks, aggregate results, manage state
• Loops, branching, conditional logic
• Human-in-the-loop checkpoints for review and approval
• Stateful long-running agents with checkpoints and resume logic

Chat Assistants and Single-Agent Flows
Chatflow provides flexible canvas for single-agent bot construction.

• RAG chatbot building with custom data
• Assistant rapid setup via forms
• Knowledge base, file, and tool attachment
• Advanced RAG with retrievers, rerankers, graph-based retrieval

Data Connectivity
Support for 100+ data formats and integration capabilities.

Supported Formats:
TXT, PDF, DOCX, HTML, CSV, MD, JSON, XML, SQL, multimedia

Vector Database Integration:
Pinecone, ChromaDB, Weaviate, Milvus, others

Deployment Options:
REST API, Python/TypeScript SDKs, web-embeddable chat widgets

Observability and Monitoring
Execution tracing visualizes step-by-step workflow progression.

• Analytics and metrics tracking (performance, token usage, costs)
• External monitoring integration (Prometheus, OpenTelemetry)
• Debugging and optimization support

Human-in-the-Loop
Task review checkpoints pause execution for human input, review, or approval.

• Stateful checkpoints surviving application restarts
• Permission controls requiring human approval for sensitive actions
• Supervision for autonomous system safety

Security and Enterprise Readiness
Role-based access control (RBAC) and Single Sign-On (SSO) for enterprise deployments.

• Encrypted credential storage for API keys and secrets
• Horizontal scalability via message queues and worker architecture
• On-premises and cloud deployment support

Extensibility
Custom node implementation for proprietary logic, models, or integrations.

• Marketplace for community-shared components
• Reusable flow templates
• Custom tool integration capabilities

Implementation Workflow

Installation:

Local/Self-Hosted:

npm install -g flowise
npx flowise start

Dashboard accessible at http://localhost:3000

Cloud Version: Register for instant setup at Flowise Cloud

Flow Creation:

1. Access dashboard (local or cloud)
2. Choose Assistant, Chatflow, or Agentflow
3. Drag and connect nodes defining workflow logic
4. Configure LLMs (OpenAI, Ollama, Claude, Llama2)
5. Integrate retrievers, databases, memory
6. Apply advanced prompts and templates

Testing and Debugging:

• Built-in chat window for live testing
• Trace execution and inspect outputs
• Profile performance and identify bottlenecks

Deployment:

• REST API for programmatic access
• SDK integration (Python, TypeScript)
• Embedded chat widget for websites
• Public URL sharing for collaboration

Common Use Cases

Enterprise Chatbots and Assistants
Automate FAQ responses, resolve support tickets, escalate complex issues. Internal knowledge base access for policy and documentation retrieval.

Multi-Agent AI Systems
Research teams with supervisor delegating information gathering to specialized worker agents. Orchestrate retrieval, summarization, analysis, reporting across agent hierarchy.

Embedded AI in SaaS Products
InsightSoftware enhanced embedded analytics with AI-driven conversational insights. UneeQ streamlined digital avatar deployment with advanced conversational AI.

Custom Integrations and Automation
Automate Notion task creation from Slack using LLM-driven bots. Multi-modal chatbots blending text and image processing.

Developer Prototyping
Drag-and-drop agent creation for hackathons, demos, production pilots. Active open-source community for flow sharing and troubleshooting.

Key Advantages

Technical Architecture

Visual Builders:

• Assistant: Form-based, rapid chatbot creation
• Chatflow: Node-based, flexible single-agent flows
• Agentflow (V2): Advanced orchestration, multi-agent collaboration, loops, branching, human-in-the-loop

LLM and Tool Integrations:

• OpenAI (GPT-3/4), Ollama (local models), Claude, Llama2
• Vector databases: Pinecone, ChromaDB, Weaviate, Milvus
• Memory implementations: Buffer, windowed, summary, custom
• API/SDK support: REST, Python, TypeScript

Security and Scalability:

• Enterprise-grade access controls (RBAC/SSO)
• Secure encrypted credential storage
• Horizontal scaling via message queues and workers

Getting Started

Installation Steps:

1. Install Node.js
2. Run: npm install -g flowise && npx flowise start
3. Access dashboard at localhost:3000
4. Or register for Flowise Cloud

First Flow Creation:

• Assistant: Fill form, attach tools and files
• Chatflow/Agentflow: Build node-based flows connecting LLMs, retrievers, memory, tools
• Test using integrated chat window
• Deploy via embed widget, API/SDK, or public link

Community Resources:

• Documentation: docs.flowiseai.com
• GitHub: github.com/FlowiseAI/Flowise
• Discord: Active community support
• Marketplace: Community flows and templates

Best Practices

Start Simple:
Begin with Assistant or Chatflow for rapid prototyping before advancing to Agentflow complexity.

Leverage Community:
Explore marketplace templates and community flows for proven patterns and accelerated development.

Implement Observability:
Use execution tracing and analytics from the start to identify bottlenecks and optimize performance.

Design for Scalability:
Plan architecture considering future growth in users, data volume, and complexity.

Secure from Start:
Implement proper access controls, encrypted credentials, and audit logging before production deployment.

Test Thoroughly:
Validate all agent behaviors, test edge cases, and ensure proper error handling and fallback logic.

Document Workflows:
Maintain clear documentation of flow logic, node configurations, and integration dependencies.

Frequently Asked Questions

How is Flowise different from n8n, Zapier, or Make.com?
Flowise specializes in agentic AI workflows with native LLM orchestration, multi-agent collaboration, RAG, and memory—features absent in general-purpose automation platforms. Open-source, self-hostable, designed for advanced AI/LLM use cases.

Can I use custom LLMs and data?
Yes. Flowise supports 100+ LLMs including local models via Ollama and open-source options. Ingests all common data formats for RAG-based flows.

Is Flowise enterprise-ready?
Yes, with RBAC, SSO, encrypted credential management, horizontal scalability, and support for on-premises and cloud deployments.

How do I contribute or get support?
Join Discord community, submit PRs or issues on GitHub, access onboarding guides in documentation.

User Testimonials

“Flowise allows us to supercharge our existing embedded analytics platform with built-in AI features that our clients absolutely love.” — Terrence Sheflin, Director of Engineering, InsightSoftware

“With Flowise, we were able to accelerate our internal ‘Build your own AI assistants easily & intuitively’ initiative. Truly a game-changer in our tech journey.” — Iokin Pardo, Senior Director, BTS Digital

“Flowise has truly changed how we approach AI. It’s simple enough to prototype an idea in minutes, yet powerful enough to take all the way to production.” — David Micotto, Senior Director of DX & AI, Publicis Groupe

References

• Flowise Official Website
• Flowise Documentation
• GitHub Repository
• Discord Community
• Flowise Cloud Marketplace
• YouTube Tutorial: Building AI Document Chatbot
• Flowise Cloud Sign Up
• Comprehensive LLM Glossary