Build LLM apps visually with a drag-and-drop interface
Flowise is an open-source low-code platform for building LLM-powered workflows and chatbots.
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AI Editor ApprovedApproved and published by our AI Editor-in-Chief after full panel analysis.Flowise is an open-source, low-code platform designed to simplify the development of applications powered by large language models (LLMs). Users build workflows by connecting pre-built nodes in a visual canvas, removing the need to write extensive boilerplate code when assembling AI pipelines. Supported use cases include retrieval-augmented generation (RAG), AI agents, multi-step chatbots, and automated data processing chains.
The platform is built on top of LangChain and LlamaIndex, two widely used open-source frameworks for LLM application development. This foundation gives Flowise access to a broad ecosystem of integrations, including support for models from OpenAI, Anthropic, HuggingFace, and others, as well as vector stores such as Pinecone, Weaviate, and Chroma. Users can also connect external APIs, databases, and tools through configurable nodes.
Flowise is self-hostable, meaning teams can deploy it on their own infrastructure for full control over data and costs. It is available as an npm package and can be run locally or on cloud platforms. A managed cloud version is also offered for users who prefer not to manage their own deployment.
The platform targets a broad audience ranging from individual developers experimenting with LLM capabilities to enterprise teams building production AI features. Its visual interface lowers the barrier to entry compared to pure code-based frameworks, while still allowing custom code nodes for advanced use cases.
In the low-code AI tooling market, Flowise competes with products such as Langflow, n8n, and Relevance AI. Its open-source nature and active community distinguish it from fully proprietary alternatives, giving users the option to inspect, modify, and self-host the software without vendor lock-in.
Build multi-agent systems with workflow orchestration distributed across multiple coordinated agents.
Build single-agent systems and chatbots with support for tool calling and knowledge retrieval (RAG) from various data sources.
Provides built-in evaluations and metrics tracking for monitoring AI application performance.
Provides full execution traces with support for Prometheus, OpenTelemetry, and other observability tools.
Allows humans to review and provide feedback on tasks performed by agents within the workflow loop.
Allows teams to create and manage unlimited workspaces for organizing AI flows and assistants.
Scales horizontally using message queues and worker processes to handle increased workloads.
Supports deployment in both cloud and on-premises environments for enterprise-grade production scaling.
Enables custom branding on embedded chatbot widgets deployed within external applications.
Supports over 100 large language models, embedding providers, and vector databases for building AI pipelines.
Extends and integrates Flowise into external applications using REST APIs, TypeScript & Python SDKs, and an embedded chat widget.
Provides role-based access control with admin roles and permissions management for team collaboration.
Individuals getting started building AI agents
For individuals & small teams
For medium-sized businesses
For specific use cases requiring dedicated support and enterprise-grade infrastructure
Workday-acquired in August 2025, Flowise turns the vendor-survival question into a roadmap-independence question.
“Flowise is the open-source, LangChain-based visual builder for LLM agents, now a Workday subsidiary as of August 2025. The decision turns less on survival and more on whether Workday's HCM roadmap drags the OSS project somewhere your team doesn't want to go.”
Workday acquired FlowiseAI in August 2025, terms undisclosed. That answers the 3-year survival question better than any pitch deck. Two co-founders out of Y Combinator's S23 batch, $500K seed, now inside a public HR platform with deep pockets.
The pull is Agentflow on top of LangChain plus 100+ model and vector-DB integrations, all self-hostable via npm. That matters for teams who want a visual canvas without surrendering data to a SaaS like Relevance AI. Pro runs $65/month for 50,000 predictions and admin roles.
However, the roadmap now belongs to Workday's HCM priorities, not the open-source community that earned the GitHub stars. Langflow is the obvious hedge if independence matters to your board. Pilot the cloud Pro tier with one team for 60 days, then decide whether to self-host.
Strongest open-source option versus Langflow and Relevance AI, but acquisition may reshape the community wedge.
Workday parent and Y Combinator pedigree make this an easy defense to the board.
npm install plus a drag-and-drop canvas gets a prototype shipping in days, not weeks.
Open-source LangChain-based agent builder fits internal AI tooling, with roadmap-drift risk under new parent.
Workday acquisition in August 2025 makes the 3-year survival question moot.
Engineering teams who want a self-hostable visual LLM builder.
Buyers who need an independent vendor with no enterprise parent.
The Workday acquisition rewrites the Flowise risk equation for any CTO scoring a 3-year LLM substrate.
“Flowise sat in the same low-code LLM lane as Langflow until Workday bought it in August 2025, which solves the survival question and reopens the lock-in one. The visual canvas, 50,000-star community, and self-host path are real assets, but the roadmap now answers to HR-suite priorities.”
Workday closed the Flowise acquisition on August 14, 2025, terms undisclosed. For a CTO scoring LLM tooling through 2028, that single event matters more than the canvas. A two-year-old YC S23 project with $500K disclosed funding is now wrapped inside a $70B HR-suite vendor.
The substrate is honest. Flowise sits on LangChain and LlamaIndex, ships as an npm package, and self-hosts cleanly with horizontal scaling via message queues. Agentflow handles multi-agent orchestration, Chatflow covers single-agent RAG. The cloud tier at $35 Starter and $65 Pro prices where SMB pilots happen.
However, the craft ceiling is the question. Langflow ships a comparable canvas, and code-first teams keep falling back to raw LangChain when visual nodes cap out. Flowise is a strong substrate for HR-adjacent agent workflows under Workday — less obviously the bet for model-native infrastructure.
Now a Workday-backed incumbent in low-code LLM tooling against Langflow, with the open-source community and 50,000 GitHub stars as moat.
The LangChain/LlamaIndex substrate plus self-host via npm matches how AI engineering teams actually prototype RAG and agents.
REST APIs, TypeScript and Python SDKs, embedded chat widget, and 100+ LLM/vector-DB connectors give the platform broad stack reach.
Workday acquisition removes survival risk but binds the 3-year roadmap to HR-suite priorities rather than AI-engineering ones.
Agentflow and Chatflow cover the two real production patterns, but visual nodes cap below what code-first agent teams need.
CTOs who need a self-hostable LLM canvas for prototyping agent workflows.
Teams who want a model-native infrastructure stack without HR-suite roadmap dependency.
Workday-backed and open-source — the $35 Starter tier is mostly a managed-hosting fee, not a license.
“Flowise prices three visible tiers from $35 to $65 monthly, with self-host always free under Apache 2.0. Workday acquired FlowiseAI in August 2025, removing the small-vendor runway risk.”
The Apache 2.0 license is the real pricing floor. Self-host costs nothing — npm install -g flowise and you're running. The $35 Starter, $65 Pro, and custom Enterprise tiers are managed-hosting fees, not software licenses. That changes the procurement conversation entirely.
Pro at $65 includes 5 seats and 50,000 predictions; additional users are $15/month each. A 20-person team lands at $65 + ($15 × 15) = $290/month, or $3,480/year. The catch is the prediction cap — no published overage rate, so a viral chatbot launch becomes an unforecastable invoice.
Workday acquired FlowiseAI in August 2025, price undisclosed. That removes the small-vendor runway risk Langflow buyers still carry. But it introduces roadmap risk — Workday will steer Agentflow toward HR and finance use cases. Self-host if your workload sits outside that lane.
Self-serve checkout on paid tiers, monthly billing, no minimum seats — minimal procurement friction.
Apache 2.0 license means the exit cost is zero — you can always fall back to self-host if cloud terms change.
Three paid tiers published at $0, $35, and $65; Enterprise requires a call but the OSS repo is the floor.
Predictions per month is a measurable unit, but no public ROI case studies tying Agentflow workflows to dollar value.
Self-host TCO is hosting plus engineering time; cloud TCO is unpredictable because there is no published overage rate above the 50,000 prediction cap.
Teams who want a self-hosted visual LLM builder with a vendor backstop.
Solo builders who do not need cloud hosting or commercial support.
Flowise's Agentflow canvas earns the LLM prototype slot, but production observability still routes through external tools.
“Agentflow and Chatflow share a canvas, so a working RAG agent and a multi-step chatbot don't fork into two stacks. The catch is the prediction meter — 10,000/month on Starter disappears under a real beta.”
Visual LLM builders usually feel like demoware until you wire a real RAG flow. Agentflow handles multi-agent orchestration in the same canvas as Chatflow, so a Pinecone-backed retriever and a tool-calling agent live side by side. Setup is `npm install -g flowise` then `npx flowise start` — local in under a minute.
The friction is the prediction meter once you leave Free. Starter at $35/month caps at 10,000 predictions; a chatbot in early beta with two concurrent users burns that before month-end. Pro at $65 lifts the ceiling to 50,000, however the trace UI pages slowly past a few thousand runs.
Execution Traces export to Prometheus and OpenTelemetry, the daily win for wiring this into existing Grafana dashboards. LangChain underneath means LangSmith works without glue. But Langflow ships a cleaner debug step-through, and version diffs on a flow JSON still mean a git diff outside the tool. Workday's August 2025 acquisition kept the open-source repo intact.
Canvas stays usable for prototyping, but the prediction meter and trace pagination start shaping daily decisions by week two.
Homepage ships the npm install snippet, docs portal exists, and the changelog is public — the team uses what they wrote.
Trace UI pages slowly past a few thousand runs and flow versioning still happens via git diff on exported JSON.
Custom code nodes, horizontal scaling via message queue, 100+ LLM/embedding/vector DB integrations, and on-prem deployment cover advanced use cases.
npm one-liner install, REST + Python/TypeScript SDKs, and Prometheus/OpenTelemetry exporters slot into existing dev infra without glue.
AI engineers who prototype RAG pipelines and tool-calling agents before committing to a code-only stack.
Teams who need polished step-through debugging and managed observability inside the platform itself.
Flowise hands you a real LLM workbench in five minutes, but the polish thins out past the canvas
“The Agentflow canvas is the heart of it — drag nodes, wire LangChain pieces, get a working agent before lunch. Past that first-day glow, the deployment story and team features feel like a different product made by a different team.”
Most low-code AI builders ship a sandbox and call it a platform. Flowise ships the workbench. The Agentflow canvas is where the real work happens — nodes for LLMs, vector stores, and tools, wired in the LangChain mental model without the boilerplate. 'npm install -g flowise' and a local instance is running before coffee.
Three days in, the cracks show. Loading inside the canvas is snappy. Loading anywhere else feels like a different team shipped it. Empty states for new workspaces are bare. The Free tier caps at 2 flows and 100 predictions monthly, fine for kicking tires. Starter at $35 jumps to 10,000 predictions, but real collaboration waits for Pro at $65.
Compared to Langflow, the open-source feel is honest — MIT license, 42K GitHub stars, an active community. However, since the Workday acquisition in August 2025, the roadmap obviously serves enterprise HR and finance priorities now. Mobile is browser-only — fair enough, nobody wires agent flows on a phone.
The Agentflow canvas is snappy but empty states and surrounding UI feel unfinished.
LangChain mental model maps cleanly to nodes; custom code nodes let depth scale past month one.
Browser-only is appropriate for an agent-building dev tool, scored neutral.
npm install -g flowise to a running local agent in minutes is a real first-hour win.
Horizontal scaling with message queues and worker processes exists for production but feel across the app is uneven.
Builders who want a visual LangChain workbench without writing boilerplate.
Teams who need a polished mobile experience today.
Workday bought it August 2025 — Apache 2.0 repo is safe, hosted product runs on Workday's clock now.
“Flowise built a real visual layer on LangChain and crossed 42,000 GitHub stars before Workday acquired it in August 2025. The catch is that the hosted tiers now compete for roadmap attention with HR and finance agent priorities.”
Workday bought Flowise on August 14, 2025. Terms undisclosed. The acquisition is the entire story — and not in the way the marketing wants.
The receipts are real. YC S23, founded by Henry Heng and Chung Yau Ong, 42,000+ GitHub stars before the deal. Built on LangChain and LlamaIndex. Starter runs $35/month for 10,000 predictions, Pro $65 for 50,000. Self-hostable via npm. Agentflow handles multi-agent orchestration; Chatflow does single-agent RAG with tool calling.
The catch is what acquisition does to indie open-source. Langflow stays independent. n8n raised a $60M Series B in March 2025. Flowise the standalone product now reports to HR and finance roadmap priorities inside Workday. Exit is genuinely clean — the repo is Apache 2.0 and forkable. Whether the hosted tiers stay sharply prioritized past 18 months is the open question.
Visual canvas is solid but Langflow and n8n cover similar ground with independent funding.
Apache 2.0 codebase, npm self-host, and LangChain underneath mean migration off the hosted tier is genuinely clean.
Workday backing helps survival; standalone-product roadmap clock just restarted under enterprise HR-finance priorities.
Pricing page lists predictions, storage, and per-user fees plainly; Apache 2.0 self-host claim holds.
42,000+ GitHub stars and a Workday acquisition match the OSS-to-enterprise-exit pattern, not the failure pattern.
Teams who want a self-hosted visual LLM workflow builder.
Buyers who need a hosted vendor with an independent roadmap.
Common questions answered by our AI research team
The Starter plan at $35/month includes 10,000 Predictions/month and 1GB Storage, while the Pro plan at $65/month includes 50,000 Predictions/month and 10GB Storage. The Pro plan also adds Unlimited Workspaces, 5 Users (plus $15/user/month for additional users), Admin Roles & Permissions, and Priority Support, none of which are included in Starter.
Yes, Flowise supports Human-in-the-Loop (HITL) functionality, described as allowing humans to review tasks performed by agents within the feedback loop.
Yes, Flowise supports on-premises deployment. The content states it offers 'on-prem & Cloud deployment' as part of its enterprise-ready, production-scale infrastructure.
Yes, getting started is as simple as running 'npm install -g flowise' followed by 'npx flowise start', as shown directly on the homepage.
Yes, Flowise provides both a Python SDK and APIs for integration. The content specifically mentions 'APIs, SDK, and Embedded Chat' with 'Typescript & Python SDKs' listed as available options for extending and integrating into your applications.
Company
FlowiseFounded
2023Pricing
From $35/moFree Plan
AvailableFlowise is an open-source, low-code tool for building LLM-powered applications and agent workflows using a drag-and-drop visual interface.
