流思人工智能
7.8

流思人工智能

  • 构建和部署 AI 无需编写任何代码即可实现可视化代理
  • 面向LLM工作流和代理系统的开源低代码平台

流水 AI 重要见解

定价模式: 车辆订阅
免费套餐: (100 Predictions/month)
标记为: Low Code / No Code AI 代理生成器
价格: 每月$ 35起
Drag and Drop Visual Builder:
多代理编排:
抹布:
LLM Model Flexibility:
Self Hosting / On Premise Deployment:
人在循环中:
API, SDK and CLI Access:
Embedded Chatbot Widget:
MCP Client/Server Integration:
Vector Database Support:
SSO / SAML Authentication:
Native Workflow Automation:
Primary LLM Framework: LangChain / LlamaIndex

What is Flowise AI?

流思人工智能

流思人工智能 is an open source, low code development platform that allows teams to build AI agents and LLM powered workflows using a visual drag and drop interface. Originally a standalone project, Flowise was acquired by Workday in August 2025 and continues to operate its cloud platform alongside its open source offering on GitHub. 

The platform supports over 100 LLMs, embedding models, and vector databases, making it one of the most flexible tools for 创建聊天机器人, RAG pipelines, and multi agent systems. Businesses use Flowise AI to prototype and ship AI applications rapidly without deep coding expertise. For teams that need full data sovereignty, Flowise supports self hosted and air gapped deployments alongside its managed cloud tiers.

Key Features of Flowise AI
可视化拖放式工作流程构建器

流水 AI provides three distinct visual builders. Assistant is the most beginner friendly option, Chatflow handles single agent systems and advanced RAG configurations, and Agentflow manages multi agent orchestration with branching, looping, and routing logic. Users connect modular nodes on a canvas to assemble full AI pipelines. This removes the need for manual coding and slashes prototyping time from weeks down to hours.

Multi Agent Systems with Workflow Orchestration
Multi Agent Systems Flowise AI

Agentflow V2 lets you distribute tasks across multiple coordinated agents. Each agent can be assigned a distinct role, tools, and instructions. The system handles handoffs, conditional routing, and parallel execution. This is the feature that separates Flowise from simpler chatbot builders and puts it in direct competition with enterprise agent platforms.

Retrieval Augmented Generation (RAG) Pipeline
Retrieval Augmented Generation Flowise AI

Flowise makes it straightforward to build RAG applications by connecting document loaders, text splitters, vector stores, and retrievers on the canvas. It supports Graph RAG, rerankers, and custom retrieval chains. You can ingest data from PDFs, databases, APIs, and more, then ground your LLM responses in your own proprietary knowledge base.

Human in the Loop Review
Human in the Loop Review Flowise AI

Production AI systems need guardrails. Flowise includes a built in HITL mechanism that allows human reviewers to approve, reject, or modify agent actions before they execute. This is essential for regulated industries and any use case where automated decisions carry real business risk.

Observability and Execution Traces
Execution Traces Flowise AI

Every workflow execution is logged with full traces. Flowise integrates with Prometheus, OpenTelemetry, and other monitoring stacks. You can visually debug agent behaviour, track token usage, and stream logs to external systems. This gives engineering teams the visibility they need to run AI in production with confidence.

API, SDK and Embedded Chat Deployment
API, SDK and Embedded Flowise AI

Once your flow is ready, Flowise generates REST API endpoints automatically. You can integrate these into any application using the TypeScript or Python SDK. The platform also provides a customisable embedded chat widget that drops into any website. This makes Flowise a genuinely full stack solution from prototype to production.

流水 AI 定价计划

计划名称成本关键限制和功能
自由$02 Flows, 100 Predictions/month, 5MB Storage, Community Support
入门版$ 35 /月Unlimited Flows, 10,000 Predictions/month, 1GB Storage, Community Support
专业版$ 65 /月50,000 Predictions/month, 10GB Storage, 5 Users (+$15/user), RBAC, Priority Support
企业版定制定价On Premise / Air Gapped, SSO/SAML, LDAP, Audit Logs, SLA Support

流水 AI Open Source Community and Ecosystem

The open source foundation of Flowise AI is one of its strongest assets. The project has amassed a large and active community on GitHub and Discord, with regular contributions from developers worldwide. The template marketplace offers pre-built flows that users can import and customise, accelerating time to value for common use cases like customer support bots, document Q&A systems, and SQL chatbots. 

Flowise also partners with vector database providers like Milvus, LLM platforms like AWS Bedrock, and frameworks like LangChain and LlamaIndex. This ecosystem means you rarely hit a dead end when integrating Flowise into an existing tech stack.

利与弊

优点
  • Genuinely visual drag and drop.
  • 100+ LLM and model integrations.
  • Strong open source community backing.
  • Self hosted and air gapped options.
  • Built in HITL and observability.
  • Multi agent orchestration support.
缺点
  • Steeper learning curve for Agentflow.
  • 没有原生移动应用。
  • Limited non AI 工作流程自动化。

Best Flowise AI 备择方案

Low Code / No Code AI 代理生成器开源灵活性企业准备情况
朗弗罗✅ MIT Licensed, graph based builderModerate, less mature enterprise tier
迪菲✅ MIT Licensed, strong app builderGood, managed cloud and self hosted
n8n✅ Fair code, broader workflow automationStrong, 400+ non AI 集成
语音流❌ Proprietary, conversation design focusStrong, dedicated enterprise plans
判决: 流水 AI wins on visual LLM flexibility and self hosting freedom.
  • 开源 AI builder trusted by Deloitte, AWS, and Accenture.
  • $ 35 /月
  • Build a production ready AI agent in under an hour. No code required.
7.0
平台安全性
9.0
无风险且退款
8.0
服务与特色
7.0
客户服务
7.8 总体评级

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流思人工智能
7.8/10
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