What Flowise is
Flowise is an Apache 2.0 licensed visual builder for LLM applications, built on Node.js and React and wrapping LangChain and LlamaIndex. You assemble chatflows by dragging nodes: a loader, a splitter, an embedding model, a vector store, a chain. For getting from nothing to a working retrieval chatbot, very little is faster.
Prototype velocity versus operating surface
Flowise and EDDI are aimed at different points in a project. Flowise optimizes the first week: visual assembly, immediate feedback, a template for most common patterns. EDDI optimizes everything after that: who may change the agent, what it is allowed to do, what happens when it restarts, and how you prove any of it to an auditor. Many teams genuinely should start in Flowise.
Prototype to production
| Dimension | Flowise | EDDI |
|---|---|---|
| Primary abstraction | Visual chatflow canvas, node graph serialized to JSON | Config-as-code: JSON resources authored in a UI or API, versioned like source |
| Runtime | Node.js event loop | JVM with virtual threads, built for many concurrent I/O-bound conversations |
| License | Apache 2.0, the same as EDDI | Apache 2.0, OSI approved |
| RAG | Broad loader and vector store selection, configured per flow | 8 embedding providers, 6 vector stores, plus zero-infrastructure httpCall RAG |
| Custom logic | Custom Function and Tool nodes execute JavaScript at runtime | Zero runtime code evaluation; logic is declared, not executed |
| Multi-tenancy | Workspaces on the enterprise edition | Per-tenant quotas, cost attribution, and data isolation in the open-source build |
| Memory | Conversation buffers and external store integrations | Persistent user memory, dream consolidation, rolling summaries, token-aware windowing |
| Audit trail | Execution traces, aimed at debugging | HMAC-signed, append-only ledger, aimed at evidence |
| Deployment | Docker, typically a single instance | Docker, Helm, Kustomize, and OpenShift (Red Hat certified image, Operator via OperatorHub) |
Details about the other tool were checked against its official documentation and repository in October 2026. These projects change quickly, so confirm current behavior with the vendor before you decide.
Choosing between them
Where Flowise is the better choice
- You are validating whether an idea works at all. Visual assembly beats configuration authoring for exploration.
- The team thinks in diagrams and wants to see the retrieval pipeline laid out spatially.
- It is an internal tool for one team, with no tenancy, audit, or approval requirements.
- You want to try five retrieval strategies before lunch.
Where EDDI is the better choice
- The chatbot became a product and now needs SLAs, tenancy, and someone accountable for changes.
- Prompt engineers must iterate without a redeploy, while operations keeps control of what ships.
- Conversations must survive restarts and be reconstructable months later for a regulator.
- A human must approve specific tool calls before the agent acts on them.
- The deployment target is Kubernetes or air-gapped infrastructure and has to be provably reproducible. 20,000+ tests run on every merge.
Moving a chatflow from Flowise
Flowise chatflows are already JSON and the concepts line up closely, so this is usually the most mechanical of the migrations.
| Flowise | EDDI |
|---|---|
| Chatflow | EDDI package, exportable as a ZIP with secrets automatically scrubbed |
| Document loaders and splitters | EDDI RAG document ingestion configuration |
| Vector store node | One of 6 supported vector stores, selected by configuration |
| Embedding node | One of 8 embedding providers |
| Chat model node | LLM configuration across 19 providers, with model cascading available |
| Custom Function node | Behavior rules, prompt snippets, or a declared MCP tool |
| Memory node | EDDI persistent memory with commit-flag memory policy |
Full playbook: migrate a chatflow from Flowise to EDDI →
Frequently asked
Should we prototype in Flowise and then move to EDDI?
That is a defensible path and a common one. Flowise answers whether a retrieval strategy works; EDDI answers whether you can operate it safely for three years. Plan the move before the prototype has production users attached, because the migration is easier than the conversation about downtime.
Both are Apache 2.0. What actually differs?
The license is the same; the operating surface is not. EDDI ships optional OIDC/Keycloak, a signed audit ledger, per-tenant quotas, and human-in-the-loop approval gating in the open-source build rather than behind an enterprise tier.
Does EDDI have a visual builder?
EDDI Manager is a production React UI for building, deploying, and monitoring agents, available in 11 languages. It is a management interface rather than a node canvas: you configure agents, prompts, tools, and pipelines, and every change is a versioned resource rather than a diagram.
Other comparisons
- EDDI vs. LangChain and LangGraph
- EDDI vs. Microsoft Agent Framework (AutoGen and Semantic Kernel)
- EDDI vs. CrewAI
- EDDI vs. Dify
- EDDI vs. n8n
- EDDI vs. Rasa
- All alternatives: builders, libraries, and cloud platforms
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