Flowise is a visual builder for creating AI agents, chatbots, RAG apps, and LLM workflows using drag-and-drop nodes.

Is Flowise open source?

Yes. Flowise has an open-source self-hosting option, while Flowise Cloud provides managed hosting and additional cloud features.

Who should use Flowise?

Flowise is best for developers and technical builders creating chatbots, RAG workflows, internal copilots, and agent prototypes.

What are predictions in Flowise?

Predictions are usage units for running flows or assistants. The Free plan lists 100 predictions per month, Starter 10,000, and Pro 50,000.

What should teams watch for?

Teams should review data security, model costs, vector database costs, workflow complexity, and plan limits before production use.

Flowise

Visual builder for AI agents, chatbots, RAG apps, and LLM workflows.

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What is Flowise?

TL;DR

Flowise is an open-source visual AI builder for creating LLM applications, RAG pipelines, chatbots, and AI agents through a node-based workflow canvas, with both self-hosted and managed cloud options.

Drag-and-drop canvas for AI agents and LLM workflows
Open-source self-hosting plus managed Flowise Cloud
Chatbots, RAG pipelines, tools, prompts, and memory nodes

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About

Flowise is a visual AI builder for creating chatbots, AI agents, retrieval pipelines, and LLM workflows with drag-and-drop nodes. It helps developers and technical teams assemble models, prompts, tools, vector stores, APIs, memory, and agent logic without building every orchestration layer from scratch. The product is useful for prototyping AI assistants, internal copilots, support bots, document Q&A apps, and workflow agents. Flowise is open source and can be self-hosted, while Flowise Cloud provides managed hosting, predictions, storage, evaluations, metrics, workspaces, and support options. Flowise is strongest for teams that want visibility into their AI application architecture. The node canvas makes it easier to understand how prompts, retrievers, tools, and models are connected, but production use still needs monitoring, prompt testing, security review, and model cost control. For FutureStack, Flowise belongs in AI Agents because it gives builders a practical visual layer for agent and LLM app development. It is best for developers who want fast prototyping with a path to self-hosted or hosted production workflows.

Use Cases

Build AI Agents

Connect models, prompts, tools, memory, and integrations visually to prototype and deploy agentic workflows.

Create RAG Apps

Build document and knowledge retrieval workflows that connect language models with vector stores and external data sources.

Prototype Chatbots

Assemble conversational assistants and internal copilots quickly using reusable nodes and model integrations.

Deploy LLM Workflows

Move from visual prototypes to managed cloud or self-hosted workflows with monitoring and production controls.

Key Features

Drag-and-drop canvas for AI agents and LLM workflows
Open-source self-hosting plus managed Flowise Cloud
Chatbots, RAG pipelines, tools, prompts, and memory nodes
Cloud plans include predictions, storage, metrics, and workspaces

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