Flowise
Open-source visual builder for AI agents and LLM workflows, Flowise lets teams and developers design, deploy, and scale chatbots and multi-agent systems with drag-and-drop, cloud or self-hosted options, and 100+ integrations.
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Key Features
Visual Builders
Drag-and-drop editor for Assistants, Chatflows, and Agentflows with branching and routing.
100+ Integrations
Supports major LLMs, embeddings, vector DBs, tools, PDFs, and APIs.
Deployment Options
Cloud, on-premise, air-gapped deployments plus TypeScript and Python SDKs.
Monitoring & Observability
Execution logs, visual debugging, evaluations, metrics, and external log streaming.
Multi-Agent Systems
Build agent architectures with memory, planning, and custom nodes.
Enterprise Security
SSO/SAML, RBAC, audit logs, versioning, input moderation, and SLA options.
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Why Choose Flowise
Rapid prototyping:
Drag-and-drop editor speeds development and testing versus hand-coding pipelines.Deployment versatility:
Choose cloud, self-hosted, or air-gapped installations with enterprise controls.Cost-effective scaling:
Free tier for exploration and predictable paid plans with defined overage rates.Extensive ecosystem:
100+ integrations and open-source extensibility for custom LLMs and tools.
Pricing
Flowise offers Free, Starter ($35/mo), Pro ($65/mo), and Enterprise (custom) plans. Free limits flows, predictions, and storage; paid plans increase prediction quotas and storage with $0.001 prediction overage. Paid plans include a 14-day free trial; Enterprise adds on-prem and SSO.
About Flowise
Open-source visual builder for AI agents and LLM workflows, Flowise lets teams and developers design, deploy, and scale chatbots and multi-agent systems with drag-and-drop, cloud or self-hosted options, and 100+ integrations.
What Flowise Does
Flowise visually builds, deploys, and scales AI agents and LLM workflows so teams can create chatbots, RAG assistants, and multi-agent systems without heavy coding. Users benefit from a drag-and-drop interface to prototype, test, and iterate agent logic quickly.
The platform orchestrates LLMs, embeddings, vector DBs, tools, and data sources via modular nodes and LangChain-compatible flows. It provides deployment options (cloud, on‑prem, air‑gapped), TypeScript/Python SDKs, APIs, observability with logs and metrics, and integrations for over 100 LLMs and services.
Common use cases include customer support bots, data analysis workflows, internal automation, and complex multi-agent coordination across product and enterprise systems.
Pros & Cons
No-code builder
Intuitive drag-and-drop interface accelerates agent development.
Open-source
Self-hosting and code-level extensibility for customization and control.
Scalable deployment
Supports prototyping through enterprise with APIs and SDKs.
Observability
Built-in logs, metrics, debugging, and monitoring integrations.
Limited free tier
Free plan caps flows, predictions, and storage, limiting production use.
Unclear overage
Prediction overage pricing ($0.001) and costs can be hard to forecast.
Technical learning
Maximizing value requires familiarity with prompts, LLMs, and integrations.
Frequently Asked Questions
Flowise's pricing model is subscription-based with Free, Starter ($35/mo), Pro ($65/mo), and Enterprise (custom) tiers; predictions count as API calls, with $0.001 overage and a 14-day free trial for paid plans.
Flowise is fully open-source and supports self-hosting alongside cloud plans, allowing source access, customization, and deployment on private infrastructure.
Flowise offers cloud-hosted, on-premise, and air-gapped deployments, plus scaling via message queues and integrations for SDKs, APIs, and observability tooling.
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