Flowise
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About
Flowise is an open-source development platform designed to facilitate the creation of agentic AI systems through a visual interface. By providing modular building blocks, it allows users to construct a wide range of AI applications, from basic compositional workflows to complex autonomous agents. The platform is built on top of LangChain, enabling developers to drag and drop different components such as Large Language Models (LLMs), vector databases, and memory modules to design their application logic visually without needing to write extensive boilerplate code. The tool distinguishes between two primary architecture types: Chatflows and Agentflows. Chatflows are designed for single-agent systems, often utilized for building chatbots with tool-calling capabilities and Retrieval-Augmented Generation (RAG) to pull data from various sources like PDFs, SQL databases, or JSON files. Agentflows enable more advanced multi-agent systems, where workflow orchestration is distributed across several coordinated agents to solve complex tasks. Beyond visual building, Flowise offers execution traces for observability, allowing teams to monitor performance using tools like Prometheus and OpenTelemetry. This platform is particularly beneficial for AI engineers, software developers, and product teams who need to iterate quickly on LLM-based solutions. While it offers a low-code environment accessible to those who prefer visual design, it remains developer-friendly by providing full APIs, Python and TypeScript SDKs, and an embeddable chat widget for seamless integration into existing software stacks. Enterprises can leverage its horizontal scaling capabilities via message queues and workers, as well as the option for on-premises deployment to maintain data privacy. Compared to other LLM orchestration tools, Flowise stands out for its extensive library of over 100 integrations and its flexible deployment model. The recent acquisition by Workday has integrated the platform into a larger enterprise ecosystem, yet it maintains its open-source roots with a strong presence on GitHub. This combination of ease-of-use for prototyping and robust infrastructure for production makes it a versatile choice for organizations of various sizes looking to implement sophisticated AI agents.
Pros & Cons
Supports over 100 LLMs, embeddings, and vector databases for high flexibility.
Provides on-premises deployment options to ensure enterprise data security.
Includes Human-In-The-Loop capabilities to allow manual review of AI tasks.
Offers full execution traces compatible with OpenTelemetry for deep debugging.
Features a very active open-source community with over 12,000 GitHub stars.
Free plan is highly restrictive with a limit of only 100 predictions per month.
The Pro plan is limited to 10GB of storage which may be low for large RAG datasets.
Additional user seats beyond the initial five on the Pro plan require a $15 per user monthly fee.
Use Cases
Software Engineers can build and test complex AI backend stacks in less than an hour using the visual drag-and-drop interface.
Customer Support Teams can embed customized, branded chatbots into their websites to automate document-based knowledge retrieval.
Data Researchers can create no-code SQL chatbots to query databases using natural language for faster data insights.
Product Managers can prototype multi-modal AI assistants that combine text and image generation without writing any code.
Enterprise Architects can deploy horizontally scalable agentic systems using message queues to handle production-level traffic.
Platform
Task
Features
• retrieval-augmented generation (rag)
• multi-agent orchestration
• horizontal scaling with message queues
• on-premises deployment support
• python & typescript sdks
• execution tracing and observability
• human-in-the-loop review
• visual drag-and-drop builder
FAQs
What is the difference between Chatflow and Agentflow in Flowise?
Chatflow is used to build single-agent systems and chatbots with support for tool calling and RAG. Agentflow is designed for multi-agent systems where orchestration is distributed across several coordinated agents.
Can I deploy Flowise on my own infrastructure?
Yes, Flowise supports both cloud and on-premises deployment. It is enterprise-ready and can scale horizontally using message queues and workers.
What integrations are supported by the platform?
Flowise supports over 100 integrations, including various LLMs, embeddings, and vector databases. It also handles numerous data formats such as PDF, SQL, JSON, and CSV.
Does Flowise offer developer tools for external applications?
Yes, it provides a full suite of developer tools including an API, Python and TypeScript SDKs, and an embeddable chat widget for website integration.
Are there observability features available for debugging flows?
Flowise provides full execution traces and supports integration with observability tools such as Prometheus and OpenTelemetry to monitor agent performance.
Pricing Plans
Starter
USD35.00 / per month• Unlimited Flows & Assistants
• 10,000 Predictions / month
• 1GB Storage
• Community Support
• Everything in Free
Pro
USD65.00 / per month• 50,000 Predictions / month
• 10GB Storage
• Unlimited Workspaces
• 5 Users included
• Admin Roles & Permissions
• Priority Support
• Everything in Starter
Free
Free Plan• 2 Flows & Assistants
• 100 Predictions / month
• 5MB Storage
• Evaluations & Metrics
• Custom Embedded Chatbot Branding
• Community Support
Job Opportunities
There are currently no job postings for this AI tool.
Ratings & Reviews
No ratings available yet. Be the first to rate this tool!
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