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Flowise vs Alteryx

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Flowise
FlowiseBuild AI Agents, Visually
Alteryx
AlteryxSelf-service data analytics platform for building and deploying machine learning models
Overview
Description

Flowise is an open-source visual builder for LLM applications and AI agents. Its drag-and-drop canvas composes chatflows and agentflows from components such as models, prompts, vector stores, tools, and memory, which can then be exposed through an API, an embeddable chat widget, or the built-in chat UI. Flowise orchestrates existing models rather than training them.

Alteryx is a data analytics platform that empowers users to build and deploy machine learning models without requiring extensive coding knowledge. It provides a user-friendly interface for data preparation, analysis, and visualization, making it an ideal solution for data analysts and business users. With Alteryx, users can connect to various data sources, create and manage workflows, and deploy models to production environments.

Pricing
Freemium

Self-hosting the open-source project is free. Flowise Cloud is tiered: Free $0/month (2 flows & assistants, 100 predictions/month, 5MB storage), Starter $35/month (unlimited flows, 10,000 predictions/month, 1GB storage), and Pro $65/month (50,000 predictions/month, 10GB storage, unlimited workspaces, +$15/user/month beyond 5 users).

Paid (Subscription)
Category
AI Productivity
Machine Learning
Best for
AI Enthusiasts and Developers
Data Analysts and Business Users
Specifications
Spec source
AI-estimated
AI-estimated
deployment
Self-hosted
Cloud/SaaS
open source
Yes
No
github stars
54,973
โ€”
api available
Yes
Yes
support options
Discord, GitHub Discussions
Email, Live Chat, 24/7 Phone Support
primary language
TypeScript
โ€”
key integrations
โ€”
Tableau, Power BI, Salesforce, Google Analytics
Pros & Cons
Pros
  • Easy to use
  • No coding required
  • Fast development and deployment
  • Collaboration features
  • Easy to use and intuitive interface
  • Fast and scalable data processing
  • Collaborative environment for team-based workflows
  • Extensive library of pre-built templates and examples
Cons
  • Behaviour beyond the built-in nodes means writing your own integrations in the components package
  • Dependent on visual interface
  • Limited support for complex AI models
  • Steep learning curve for advanced features
  • Steep learning curve for advanced features
  • Limited customization options for workflows and dashboards
  • Dependent on cloud connectivity for full functionality
Community & Metrics
Upvotes
0
0
User rating
Not enough data
Not enough data

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Flowise
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Build AI Agents, Visually

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