Skip to main content
aitoolsatlas.ai
BlogAbout

Explore

  • All Tools
  • Comparisons
  • Best For Guides
  • Blog

Company

  • About
  • Contact
  • Editorial Policy

Legal

  • Privacy Policy
  • Terms of Service
  • Affiliate Disclosure
Privacy PolicyTerms of ServiceAffiliate DisclosureEditorial PolicyContact

© 2026 aitoolsatlas.ai. All rights reserved.

Find the right AI tool in 2 minutes. Independent reviews and honest comparisons of 890+ AI tools.

  1. Home
  2. Tools
  3. Flowise
OverviewPricingReviewWorth It?Free vs PaidDiscountAlternativesComparePros & ConsIntegrationsTutorialChangelogSecurityAPI
AI App Builder🟡Low Code
F

Flowise

Flowise is an open-source visual builder for LLM apps, RAG pipelines, and multi-agent workflows that you can self-host for free or run on Flowise Cloud.

Starting atFree
Visit Flowise →
💡

In Plain English

Flowise is an open-source visual builder for LLM apps, RAG pipelines, and multi-agent workflows that you can self-host for free or run on Flowise Cloud.

OverviewFeaturesPricingGetting StartedUse CasesIntegrationsLimitationsFAQSecurityAlternatives

Overview

Flowise is an Apache-2.0 licensed visual LLM and agent builder. Drag-and-drop canvas for chains, RAG, and multi-agent flows on top of LangChain and LlamaIndex, with broad model and vector store support. Self-host free or run on Flowise Cloud. MCP client support is built in.

🦞

Using with OpenClaw

▼

Integrate Flowise with OpenClaw through available APIs or create custom skills for specific workflows and automation tasks.

Use Case Example:

Extend OpenClaw's capabilities by connecting to Flowise for specialized functionality and data processing.

Learn about OpenClaw →
🎨

Vibe Coding Friendly?

▼
Difficulty:beginner
No-Code Friendly ✨

Standard web service with documented APIs suitable for vibe coding approaches.

Learn about Vibe Coding →

Was this helpful?

Editorial Review

Strong bridge between low-code builders and developer-owned LangChain-style workflows. Main caution: The /pricing route redirected to sign-in during research, so pricing should be manually verified before publishing.

Key Features

Agentflow for Multi-Agent Orchestration+

Build multi-agent systems with workflow orchestration distributed across multiple coordinated agents. Each agent can have its own tools, memory, and instructions, with handoffs between agents for complex task decomposition.

Chatflow with RAG and Tool Calling+

Build single-agent systems and chatbots with support for tool calling and knowledge retrieval (RAG) from various data sources. Supports document formats including TXT, PDF, RTF, DOC, HTML, CSV, MD, and SQL.

Human-in-the-Loop (HITL) Workflows+

Allow humans to review tasks performed by agents within the feedback loop before final execution. This is critical for regulated industries and high-stakes decisions where AI outputs need human validation.

Observability with Execution Traces+

Full execution traces support Prometheus, OpenTelemetry, and other observability tools out of the box. Track every node execution, LLM call, tool invocation, and token usage across your workflows.

Developer-Friendly API, SDK, and Embed+

Extend and integrate to your applications using REST APIs, TypeScript and Python SDKs, and an embeddable chat widget. Deploy any chatflow as a /api/v1/prediction/:id endpoint with a single click.

Pricing Plans

Open Source

Free

    Cloud Starter

    From $35/month

      Cloud Pro

      From $65/month

        Enterprise

        Contact sales

          See Full Pricing →Free vs Paid →Is it worth it? →

          Ready to get started with Flowise?

          View Pricing Options →

          Getting Started with Flowise

          1. 1Install Flowise locally via npm (npm install -g flowise) or use Docker deployment with official flowise/flowise image
          2. 2Launch Flowise server and navigate to http://localhost:3000 to access the visual builder interface
          3. 3Configure your first LLM provider (OpenAI, Anthropic, or local Ollama) by adding API credentials in the settings
          4. 4Create your first chatflow by dragging a Chat Model node and connecting it to a Simple Chain for basic functionality
          5. 5Test your chatflow using the built-in chat interface, then deploy as API endpoint with one-click deployment
          Ready to start? Try Flowise →

          Best Use Cases

          🎯

          Internal RAG chatbots over docs, Confluence, or Notion

          ⚡

          Customer-support bots with tool calls and escalation

          🔧

          Prototype agentic workflows before a code-first rewrite

          🚀

          Multi-step extraction pipelines from PDFs or webpages

          💡

          Demos for non-technical stakeholders showing how an agent reasons

          Integration Ecosystem

          33 integrations

          Flowise works with these platforms and services:

          🧠 LLM Providers
          OpenAIAnthropicGoogleCohereMistralOllama
          📊 Vector Databases
          PineconeWeaviateQdrantChromaMilvuspgvector
          ☁️ Cloud Platforms
          AWSGCPAzureRailway
          💬 Communication
          SlackDiscordEmailTwilio
          📇 CRM
          HubSpot
          🗄️ Databases
          PostgreSQLMySQLMongoDBSupabase
          📈 Monitoring
          LangSmithLangfuse
          💾 Storage
          S3
          ⚡ Code Execution
          Docker
          🔗 Other
          GitHubNotionZapierMake
          View full Integration Matrix →

          Limitations & What It Can't Do

          We believe in transparent reviews. Here's what Flowise doesn't handle well:

          • ⚠Cannot export chatflows as standalone code — applications must run within the Flowise runtime environment
          • ⚠Custom components require TypeScript development knowledge and understanding of Flowise's specific node architecture
          • ⚠No built-in evaluation or testing framework — quality assessment requires external tooling like LangSmith or manual testing
          • ⚠Scaling beyond a single instance requires manual load balancing configuration and shared PostgreSQL/storage setup
          • ⚠Visual canvas becomes cluttered with workflows containing many conditional branches or 50+ nodes, reducing maintainability

          Pros & Cons

          ✓ Pros

          • ✓Truly open source; self-host gives you full control of data and prompts
          • ✓Visual canvas dramatically shortens the prototype-to-demo loop
          • ✓Huge integration surface inherited from LangChain and LlamaIndex
          • ✓MCP client support means new tool ecosystems plug in without code
          • ✓Active community: 30k+ GitHub stars, frequent releases, Discord support

          ✗ Cons

          • ✗Visual graphs get unwieldy at scale; complex flows can become hard to maintain
          • ✗Some breaking changes between versions; pin and test before upgrading
          • ✗Observability and evals are basic compared to dedicated platforms
          • ✗Production deployment (auth, rate limiting, monitoring) is on you for self-host
          • ✗Cloud pricing is competitive but execution limits can bite for chatty agents

          Frequently Asked Questions

          Do I need to know LangChain to use Flowise?+

          It helps significantly. Flowise visualizes LangChain/LlamaIndex components — understanding what a retriever, chain, or agent does makes the visual builder much more effective. You can start with simple chatflows using pre-built templates, but deeper customization benefits from framework knowledge.

          How does Flowise compare to Langflow?+

          Both are visual LangChain builders, but they target different ecosystems. Flowise is Node.js-based, while Langflow is Python-based — important for deployment preferences and team skill sets.

          Can I export Flowise chatflows as code?+

          Flowise doesn't directly export chatflows as standalone Python/TypeScript code. Chatflows are stored as JSON configurations that Flowise interprets at runtime via its Node.js engine. If you need standalone code, use the chatflow design as a reference to implement equivalent logic directly with LangChain.

          What's the best way to deploy Flowise in production?+

          Docker deployment on a cloud VM or container platform (AWS ECS, Google Cloud Run, Kubernetes) is the most common production approach. Use PostgreSQL for persistent storage of chatflow configurations and conversation history.

          Is Flowise free to use, and what does the enterprise version offer?+

          Yes, Flowise is fully open-source and free to self-host via npm or Docker — install it with a single command (npm install -g flowise) and run npx flowise start. The enterprise tier adds managed hosting, SSO, advanced security, and dedicated support.

          🔒 Security & Compliance

          —
          SOC2
          Unknown
          —
          GDPR
          Unknown
          —
          HIPAA
          Unknown
          —
          SSO
          Unknown
          ✅
          Self-Hosted
          Yes
          ✅
          On-Prem
          Yes
          ✅
          RBAC
          Yes
          —
          Audit Log
          Unknown
          ✅
          API Key Auth
          Yes
          ✅
          Open Source
          Yes
          —
          Encryption at Rest
          Unknown
          ✅
          Encryption in Transit
          Yes
          Data Retention: configurable
          Data Residency: SELF-HOSTED DEPLOYMENTS ALLOW USER-CONTROLLED DATA RESIDENCY

          Recent Updates

          View all updates →
          🔄

          Multi-Agent Workflows

          v2.1.0

          Visual builder support for multi-agent conversations and handoffs.

          Feb 14, 2026Source
          🦞

          New to AI tools?

          Read practical guides for choosing and using AI tools

          Read Guides →

          Get updates on Flowise and 370+ other AI tools

          Weekly insights on the latest AI tools, features, and trends delivered to your inbox.

          No spam. Unsubscribe anytime.

          What's New in 2026

          Flowise has expanded its Agentflow capabilities for multi-agent orchestration, added Human-in-the-Loop (HITL) workflows for regulated industries, and improved observability with Prometheus and OpenTelemetry support. The platform continues to grow its community marketplace and component library.

          Alternatives to Flowise

          CrewAI

          AI Agents

          Open-source Python framework for orchestrating role-playing, autonomous AI agents that collaborate as a 'crew' to complete complex tasks.

          Microsoft AutoGen

          Multi-Agent Builders

          Microsoft's open-source framework for building multi-agent AI systems with asynchronous, event-driven architecture.

          LangGraph

          AI agent framework

          LangGraph is LangChain's open-source framework for building stateful, durable, multi-agent workflows in Python and JavaScript with graph-based control flow.

          Microsoft Semantic Kernel

          AI Agent Builders

          SDK for building AI agents with planners, memory, and connectors. - Enhanced AI-powered platform providing advanced capabilities for modern development and business workflows. Features comprehensive tooling, integrations, and scalable architecture designed for professional teams and enterprise environments.

          View All Alternatives & Detailed Comparison →

          User Reviews

          No reviews yet. Be the first to share your experience!

          Quick Info

          Category

          AI App Builder

          Website

          flowiseai.com
          🔄Compare with alternatives →

          Try Flowise Today

          Get started with Flowise and see if it's the right fit for your needs.

          Get Started →

          Need help choosing the right AI stack?

          Take our 60-second quiz to get personalized tool recommendations

          Find Your Perfect AI Stack →

          Want a faster launch?

          Explore 20 ready-to-deploy AI agent templates for sales, support, dev, research, and operations.

          Browse Agent Templates →

          More about Flowise

          PricingReviewAlternativesFree vs PaidPros & ConsWorth It?Tutorial

          📚 Related Articles

          Best No-Code AI Agent Builders in 2026: Complete Platform Comparison

          An honest comparison of the best no-code AI agent builders: n8n, Flowise, Dify, Langflow, Make, Zapier, and more. Features, pricing, agent capabilities, and recommendations by use case.

          2026-03-127 min read

          AI Agent Tooling Trends to Watch in 2026: What's Actually Changing

          The 10 trends reshaping the AI agent tooling landscape in 2026 — from MCP adoption to memory-native architectures, voice agents, and the cost optimization wave. With real tools leading each trend and current market data.

          2026-03-1716 min read

          How to Build AI Apps Without Code: Dify Tutorial & Review [2026]

          A hands-on tutorial for building production AI apps with Dify — no coding required. Covers setup, three real use cases (customer support bot, document QA, content pipeline), pricing, and how it compares to LangChain and Flowise.

          2026-04-1514 min read