Business automation · Decision brief
Alfe vs n8n
A persistent hosted agent, not a workflow you assemble node-by-node.
n8n is a visual automation canvas where AI-agent nodes execute on a trigger, on n8n Cloud or your own infrastructure. Alfe runs a persistent, code-grade agent on its own dedicated server — with pooled model access across 9 providers on one credit pool, managed vector + knowledge-graph memory, teams and fleets, and voice.
Alfe
Managed agent OS
Best when you need
A persistent agent with compute, models, memory, identity and channels managed together.
n8n
Business automation
Best when you need
Self-hosted visual automation workflows.
The short answer
Which one fits the job?
These products often sit at different layers of the stack. The useful question is not which has more ticks—it is whether you want to assemble the system or operate a finished agent.
Choose Alfe when
An agent, not a workflow graph
n8n is a canvas where you wire AI-agent nodes into a flow that fires on a trigger. Alfe runs a persistent, code-grade agent (OpenClaw or Hermes) on its own dedicated server — always on, crash-recovered, with its own memory and identity — rather than a workflow that spins up per execution.
One credit pool across 9 providers
n8n's LLM nodes are provider-agnostic, but you bring and manage each provider's key, and n8n Cloud meters by workflow executions. Alfe routes 9 model providers through one proxy and meters everything into a single prepaid USD credit pool — no per-key wrangling, one bill, bounded spend.
Memory that persists by default
n8n's default "Simple Memory" isn't persisted across sessions — real persistence means standing up an external store like Postgres and wiring a Chat Memory node. Alfe ships managed semantic vectors plus a knowledge graph out of the box: persistent, queryable memory with an interactive memory-map view in the dashboard.
Choose n8n when
- Self-host & source availability: Source-available (Sustainable Use License); free self-hostable Community Edition
- MCP support: Native MCP on both sides — MCP Server Trigger node + MCP Client node
- Breadth of connectors: 400+ connectors (500+ marketed) plus provider-agnostic LLM nodes
Capability matrix
Alfe and n8n, side by side.
A practical comparison of product shape, operations and the capabilities a team receives without additional assembly.
| Capability | Alfe | n8n |
|---|---|---|
| Self-host & source availability | AlfeProprietary managed platform — not self-hostable, not open source | n8nSource-available (Sustainable Use License); free self-hostable Community Edition |
| Runtime model | AlfePersistent per-agent server running a code-grade agent (OpenClaw / Hermes), crash-recovered | n8nVisual workflow canvas; AI-agent nodes execute per run on your instance |
| Model access & billing | AlfePooled proxy across 9 providers on one USD credit pool, BYOK + approved-model policy | n8nProvider-agnostic LangChain LLM nodes (OpenAI, DeepSeek, Gemini, Groq, Azure); you supply each key |
| Managed memory | AlfeSemantic vectors + a knowledge graph, managed and persistent | n8nMemory sub-nodes; default "Simple Memory" isn't persisted — persistence needs Postgres |
| MCP support | AlfeNative MCP — agents self-bootstrap over mcp.alfe.ai and claim their own compute | n8nNative MCP on both sides — MCP Server Trigger node + MCP Client node |
| Breadth of connectors | Alfe40+ ecosystem integrations, installable from the dashboard | n8n400+ connectors (500+ marketed) plus provider-agnostic LLM nodes |
| Teams, orgs & fleets | AlfeFull org hierarchy with roles, plus fleets of dedicated per-agent runtimes | n8nUnlimited users and workflows per instance; no fleet of dedicated agent runtimes |
| Per-agent identity | AlfeOAuth-provisioned per-agent bots and credentials | n8nCredentials configured on the instance and shared across workflows |
| Channels & voice | AlfeSlack, Discord, Teams, Google Chat, web, mobile — plus voice, SMS & WhatsApp on a real number | n8nReaches channels through connector nodes; no built-in agent voice/phone presence |
| Pricing model | AlfeOne prepaid USD credit pool funds compute, models, voice, and channels | n8nCloud metered by workflow executions (Starter €20 / Business €667), or free self-host |
Where Alfe differs
The operating layer is the product.
An agent, not a workflow graph
n8n is a canvas where you wire AI-agent nodes into a flow that fires on a trigger. Alfe runs a persistent, code-grade agent (OpenClaw or Hermes) on its own dedicated server — always on, crash-recovered, with its own memory and identity — rather than a workflow that spins up per execution.
One credit pool across 9 providers
n8n's LLM nodes are provider-agnostic, but you bring and manage each provider's key, and n8n Cloud meters by workflow executions. Alfe routes 9 model providers through one proxy and meters everything into a single prepaid USD credit pool — no per-key wrangling, one bill, bounded spend.
Memory that persists by default
n8n's default "Simple Memory" isn't persisted across sessions — real persistence means standing up an external store like Postgres and wiring a Chat Memory node. Alfe ships managed semantic vectors plus a knowledge graph out of the box: persistent, queryable memory with an interactive memory-map view in the dashboard.
Omnichannel presence, including voice
n8n reaches messaging apps through connector nodes inside a workflow. Alfe gives each agent a real presence across Slack, Discord, Teams, Google Chat, web, and mobile — plus streaming voice, SMS, and WhatsApp on a real phone number — as first-class channels, not steps in a flow.
Where n8n genuinely wins
n8n is source-available and self-hostable for free under the Sustainable Use License, with a huge connector catalogue (400+, 500+ marketed) and native MCP on both sides. If you want to own the infrastructure and wire internal automations yourself, that's a real strength Alfe doesn't match — Alfe is a paid, managed platform, not open source.
How this comparison is made
Transparent by design.
This is a first-party Alfe comparison, not an independent review. We assess product positioning, hosting, model billing, memory, MCP, team controls and channels against publicly available product information. Products change; use the official source below for the latest detail.
Read n8n documentation Compared with Alfe · n8nQuestions teams ask
Alfe vs n8n FAQ.
Is Alfe an n8n alternative?
For agents, yes — with a different shape. n8n is a workflow-automation canvas where AI-agent nodes execute on a trigger. Alfe is a persistent hosted agent on its own server, with pooled model access across 9 providers, managed vector + knowledge-graph memory, teams and fleets, and voice. n8n is stronger if you want to self-host and wire automations node-by-node.
Is n8n open source, and is Alfe?
Neither is OSI open source. n8n is source-available under the Sustainable Use License v1.0 and self-hostable for free, though it restricts commercial redistribution. Alfe is a proprietary, paid, managed platform — not self-hostable and not open source.
Do both support MCP?
Yes. n8n has native MCP on both sides — an MCP Server Trigger node and an MCP Client node. Alfe is also MCP-native and goes further with self-bootstrap: an agent can discover the platform over mcp.alfe.ai and claim its own compute and identity.
How does memory differ?
n8n's default "Simple Memory" isn't persisted across sessions; durable memory means adding an external store like Postgres. Alfe ships managed, persistent semantic vectors plus a knowledge graph by default — no external database to provision.
Keep comparing
Explore adjacent choices.
Ready to run
Move from a workflow canvas to a real agent.
Get a dedicated per-agent server, pooled model access on one credit pool, managed memory, teams, and voice — managed for you, or bring the agent you already run.