Flowise
Assemble chatbots and multi-agent workflows on a drag-and-drop canvas without writing backend code. Acquired by Workday in August 2025 and being integrated into their platform.
The verdict on Flowise: Developers who want to build LLM pipelines visually instead of writing LangChain code directly Flowise is a drag-and-drop node interface over LangChain, which means the chains, agents, and RAG pipelines available are real, just wired together without a coding layer. Pricing: Free (self-host) / Free tier Cloud / $35/mo Starter.
Best For
Developers who want to build LLM pipelines visually instead of writing LangChain code directly
Standout Feature
A drag-and-drop node interface exposing chains, agents, and RAG pipelines without a coding layer
TL;DR
Genuinely useful for no-code LLM workflows, complex flows still get hard to debug visually.
Alternatives
Fit Score: use-case reference
How this is scoredFlowise scored 1 to 5 on five dimensions for the named use cases below. Part of our catalog-wide use-case reference, not a product-quality review rating.
Developers building LLM pipelines visually instead of writing LangChain code directly
4.4/5- Capability
- 5/5
- Reliability
- 4/5
- Value
- 5/5
- Ease
- 4/5
- Compatibility
- 4/5
No code is required for complex LLM workflows, and a huge library of pre-built nodes plus an active open-source community make Flowise strong for visual pipeline building.
Debugging complex flows or fine-tuning performance without LangChain knowledge
2.2/5- Capability
- 2/5
- Reliability
- 2/5
- Value
- 3/5
- Ease
- 2/5
- Compatibility
- 2/5
Complex flows can be hard to debug visually, and performance tuning requires understanding the underlying LangChain, per its own cons.
Editorial judgment grounded in this tool's own published pricing, features, and our existing pros and cons, not a certification or a measured benchmark. Product quality is assessed separately under our review methodology.
Overview
Not yet reviewedProduct quality is assessed from original evidence. How reviews work.
Flowise is an open-source visual builder for LLM applications that uses a drag-and-drop node interface to wire together language models, vector stores, retrievers, memory modules, and external tools into complete AI pipelines without requiring code for the configuration layer. Built on top of LangChain's primitives, Flowise exposes chains, agents, RAG pipelines, and tool-using systems as configurable visual flows, making LLM application architecture understandable and modifiable by team members without deep framework expertise. Teams use it to build: customer support chatbots trained on company documentation, internal research assistants grounded in organizational knowledge bases, multi-step research agents that combine web search with document retrieval, and API-integrated workflows that connect LLM processing with business system actions. The node library covers all major LLM providers, vector database integrations, document loaders, text splitters, memory types, and tool connectors, providing components for complete application construction.
Self-hosted deployment requires Docker and a supported database; the setup process is well-documented and straightforward for teams comfortable with containers. Flowise Cloud provides a managed version for teams without infrastructure management resources. The embedded chat widget deploys finished applications as a chatbot on any website. With over 38,000 GitHub stars, Flowise is among the most-used open-source LLM builders, particularly for teams who want LangChain's capabilities through a visual interface rather than code.
The source of the legacy catalog rating and review count has not been substantiated. Neither is presented here as a verified review rating or included in review structured data.
Workflow Fit Scores are separate, use-case-specific editorial judgments, not user-review averages. Read the Fit Score methodology.
- • No code required for complex LLM workflows
- • Huge library of pre-built nodes
- • Active open-source community
- • Complex flows can be hard to debug visually
- • Performance tuning requires understanding underlying LangChain
Key Features
- Visual flow editor
- 100+ built-in integrations
- RAG pipeline support
- Agent and tool chaining
- Self-hostable
- API deployment
Trust & Data
Verified 2026-09
- Training on your data
- Not publishedFlowise's terms grant a license to use submitted content solely to operate and improve the services, and state only anonymized, aggregated usage data may be used for platform improvement; neither document explicitly addresses AI model training on user content. Self-hosted Flowise collects no metrics or data at all, per the vendor's own privacy policy.
- Compliance
- Not published
- Retention
- Personal data is retained only as long as needed for the stated purposes or as required by law; anonymized data may be retained indefinitely.
- Export
- Partial export
Sources: flowiseai.com/privacy, flowiseai.com/terms
As published by the vendor. Verify independently before purchase decisions.
Our Take
The acquisition by Workday in August 2025 adds long-term platform questions worth tracking, though the product continues operating. The honest limit is debugging: complex visual flows get hard to trace when something breaks, and performance tuning still requires understanding the underlying LangChain behavior. This fits a developer who wants to build and iterate on LLM pipelines without writing backend configuration code, accepting that deep customization will eventually require going under the canvas.