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FlowiseAI

Paid

Build AI Agents, Visually

4.5
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Inputs: textOutputs: text
Type
Saas
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About FlowiseAI

Flowise is an open-source, low-code platform designed for building AI agents and agentic systems visually. It provides modular building blocks that allow users to create everything from simple chatbots to complex multi-agent workflows with orchestration. Key capabilities include support for tool calling, retrieval-augmented generation (RAG) from various data sources (TXT, PDF, DOC, HTML, etc.), human-in-the-loop review, observability with execution traces, and developer-friendly APIs, SDKs, and embedded widgets. The platform integrates with over 100 LLMs, embeddings, and vector databases, and supports scalable enterprise deployment on cloud or on-premises. Flowise is trusted by teams globally, as evidenced by customer success stories highlighting its use in embedded analytics, digital human experiences, copilot features, and internal AI assistant initiatives.

Key Features

Visual building blocks for agentic systems
Multi-agent systems with workflow orchestration
Single-agent chatbots with tool calling and RAG
Human-in-the-loop (HITL) task review
Observability with full execution traces (Prometheus, OpenTelemetry)
Developer-friendly API, SDK, and embedded chat widget
Enterprise-grade deployment (cloud and on-premises)
Support for 100+ LLMs, embeddings, and vector databases
Horizontal scaling with message queue and workers
File ingestion from TXT, PDF, RTF, DOC, HTML, CSS, JS, JSON, XML, CSV, MD, SQL

Pros & Cons

Pros
  • Open-source with active community on Discord and GitHub
  • Low-code visual builder reduces development time
  • Modular and extensible with support for many LLMs and data sources
  • Includes human-in-the-loop for safe agent task execution
  • Offers observability and detailed execution traces
  • Scalable enterprise infrastructure with cloud/on-prem deployment
  • Clear tiered pricing with a free plan to start
  • Developer-friendly APIs, SDKs, and embedded chat options
Cons
  • Free tier limited to 2 flows, 100 predictions/month, and 5MB storage
  • Higher tiers needed for significant scale and team collaboration
  • May require some technical understanding for complex multi-agent setups

Best For

Supercharging embedded analytics platforms with AI featuresOrchestrating AI for digital human experiencesEnhancing copilot features in fleet management productsBuilding internal AI assistant initiativesCreating AI persona bots and teaching-style chatbotsDeveloping production-ready chatbots and retrieval-augmented generation (RAG) applications

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