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Flowise

FlowiseAI

78·Strong

Overall Trust Score

Open-source low-code platform for building customized LLM orchestration flows and AI agents. Visual node-based editor for creating RAG pipelines, chatbots, and autonomous agents without extensive coding.

visual
low-code
open-source
Version: 2.x
Last Evaluated: November 9, 2025
Official Website →

Trust Vector

Performance & Reliability

78
node execution
80
Methodology
Flow execution testing
Evidence
Flowise Documentation
Node-based execution with sequential and parallel flows
Date: 2024-10-20
Confidence: highLast verified: 2025-11-09
llm chain support
85
Methodology
LLM chain testing
Evidence
LangChain Integration
Built on LangChain with support for chains and agents
Date: 2024-10-15
Confidence: highLast verified: 2025-11-09
chatflow management
82
Methodology
Chatflow capability assessment
Evidence
Chatflows
Multiple chatflows with API endpoints and embeddings
Date: 2024-10-01
Confidence: highLast verified: 2025-11-09
vector store support
86
Methodology
Vector store integration testing
Evidence
Vector Stores
Multiple vector stores: Pinecone, Weaviate, Qdrant, Chroma
Date: 2024-10-01
Confidence: highLast verified: 2025-11-09
error handling
71
Methodology
Error recovery testing
Evidence
Error Management
Basic error handling with visual feedback
Date: 2024-09-20
Confidence: mediumLast verified: 2025-11-09
latency
Value: 500ms-8s (varies)
Methodology
Performance monitoring
Evidence
Performance
Depends on LLM calls, vector searches, and chain complexity
Date: 2024-10-01
Confidence: mediumLast verified: 2025-11-09

Security

73
api authentication
76
Methodology
Authentication testing
Evidence
API Security
API key authentication for chatflows and predictions
Date: 2024-10-01
Confidence: mediumLast verified: 2025-11-09
self hosting
88
Methodology
Deployment security assessment
Evidence
Deployment
Self-hosting via Docker, npm, or cloud platforms
Date: 2024-10-01
Confidence: highLast verified: 2025-11-09
credential management
74
Methodology
Credential security review
Evidence
Credentials
Encrypted credential storage with environment variables
Date: 2024-10-01
Confidence: mediumLast verified: 2025-11-09
open source
90
Methodology
Open source assessment
Evidence
GitHub
Apache 2.0 license, 32k+ stars, active development
Date: 2024-10-20
Confidence: highLast verified: 2025-11-09
data isolation
68
Methodology
Data isolation assessment
Evidence
Architecture
Basic isolation, enterprise features limited
Date: 2024-10-01
Confidence: mediumLast verified: 2025-11-09

Privacy & Compliance

79
data retention
82
Methodology
Privacy architecture review
Evidence
Chat History
Configurable chat history storage and retention
Date: 2024-10-01
Confidence: mediumLast verified: 2025-11-09
gdpr compliance
78
Methodology
Compliance capabilities assessment
Evidence
Self-Hosted
GDPR compliance possible with self-hosted deployment
Date: 2024-10-01
Confidence: mediumLast verified: 2025-11-09
local deployment
90
Methodology
Deployment options assessment
Evidence
Local Installation
Easy local deployment with Docker or npm
Date: 2024-10-01
Confidence: highLast verified: 2025-11-09
llm data sharing
73
Methodology
Data flow analysis
Evidence
LLM Integration
Data sent to configured LLM providers
Date: 2024-10-01
Confidence: mediumLast verified: 2025-11-09
embedding storage
76
Methodology
Data storage assessment
Evidence
Vector Stores
Control over vector store selection and data storage
Date: 2024-10-01
Confidence: mediumLast verified: 2025-11-09

Trust & Transparency

84
documentation quality
86
Methodology
Documentation completeness review
Evidence
Flowise Docs
Comprehensive docs with examples and video tutorials
Date: 2024-10-20
Confidence: highLast verified: 2025-11-09
visual interface
90
Methodology
UI/UX assessment
Evidence
UI Features
Intuitive drag-and-drop visual interface
Date: 2024-10-01
Confidence: highLast verified: 2025-11-09
open source
92
Methodology
Open source assessment
Evidence
GitHub
Apache 2.0, 32k+ stars, very active community
Date: 2024-10-20
Confidence: highLast verified: 2025-11-09
community support
82
Methodology
Community engagement analysis
Evidence
Community
Active Discord and GitHub discussions
Date: 2024-10-20
Confidence: highLast verified: 2025-11-09
chatflow export
76
Methodology
Portability assessment
Evidence
Import/Export
Export chatflows as JSON for portability
Date: 2024-10-01
Confidence: mediumLast verified: 2025-11-09

Operational Excellence

76
ease of use
93
Methodology
Usability assessment
Evidence
User Experience
Very intuitive for non-technical users
Date: 2024-10-01
Confidence: highLast verified: 2025-11-09
scalability
68
Methodology
Scalability testing
Evidence
Scaling
Basic scaling support, requires container orchestration
Date: 2024-10-01
Confidence: mediumLast verified: 2025-11-09
cost predictability
92
Methodology
Pricing model analysis
Evidence
Open Source
Free Apache 2.0, costs only for hosting and LLM APIs
Date: 2024-10-01
Confidence: highLast verified: 2025-11-09
monitoring
65
Methodology
Monitoring features assessment
Evidence
Monitoring Features
Basic chat history and logs, limited monitoring
Date: 2024-10-01
Confidence: mediumLast verified: 2025-11-09
api deployment
80
Methodology
API capabilities assessment
Evidence
API Endpoints
Chatflows auto-generate API endpoints
Date: 2024-10-01
Confidence: highLast verified: 2025-11-09
marketplace
78
Methodology
Template ecosystem assessment
Evidence
Templates
Growing marketplace of pre-built chatflows
Date: 2024-10-01
Confidence: highLast verified: 2025-11-09

✨ Strengths

  • •Extremely user-friendly visual interface for building AI agents
  • •Open source (Apache 2.0) with very active community (32k+ stars)
  • •Easy deployment with Docker, npm, or cloud platforms
  • •Built-in support for multiple vector stores and LLM providers
  • •Auto-generates API endpoints for chatflows
  • •Growing marketplace of pre-built templates and use cases

⚠️ Limitations

  • •Limited enterprise features (advanced auth, monitoring, RBAC)
  • •Primarily designed for prototyping and small-scale deployment
  • •Performance optimization requires technical knowledge
  • •Security features less mature than enterprise platforms
  • •Scaling to high-volume production requires additional infrastructure
  • •Limited debugging capabilities for complex flows

📊 Metadata

license: Apache 2.0
supported models:
0: OpenAI
1: Anthropic
2: Google
3: Azure OpenAI
4: HuggingFace
5: Ollama
programming languages:
0: TypeScript
1: JavaScript
deployment type: Self-hosted (Docker, npm) or cloud
tool support:
0: LangChain tools
1: Custom nodes
2: API integrations
pricing model: Free open source (FlowiseAI Cloud managed service available)
github stars: 42000+
first release: 2023
vector stores: Pinecone, Weaviate, Qdrant, Chroma, Supabase, Postgres
ui technology: React-based visual node editor
acquisition: Acquired by Workday in August 2025
version: 3.0.1+

Use Case Ratings

customer support

84

Excellent for building support chatbots with visual interface

code generation

70

Can build code agents but limited specialized capabilities

research assistant

86

Strong for RAG-based document Q&A and summarization

data analysis

73

Can integrate analysis tools via LangChain nodes

content creation

79

Good for building content generation workflows

education

87

Ideal for educators building AI tutors without coding

healthcare

72

Prototyping suitable, production needs hardening

financial analysis

70

Self-hosted option but limited enterprise features

legal compliance

81

Good for document analysis with vector search

creative writing

77

Suitable for creative prompt engineering workflows