What’s the difference between Lindy and n8n?
Lindy is a goal-driven AI agent platform where you describe what you want done, give the agent a set of allowed tools and credentials, and the agent decides the steps. n8n is a visual workflow runtime where you explicitly compose nodes — including AI agent nodes — into a directed graph. For judgment-heavy work where the steps aren’t fixed: Lindy. For deterministic workflows where you want explicit control: n8n.
TL;DR
Both products can do “AI-driven automation,” but the abstraction layer is different.
- Lindy is agent-first. You write a goal in natural language, attach tools (Gmail, calendar, CRM, Slack), and the agent decides what to call when. Each “task” is one agent invocation.
- n8n is workflow-first. You compose a directed graph of nodes, and AI is one type of node among many. You decide what runs when. Self-hosting is a first-class deployment.
For work where the right action depends on the situation (qualify this lead, decide which inbox replies need a draft), Lindy is the sharper tool. For work where the steps are known (every Monday, copy data from A to B), n8n is the cleaner tool.
How to think about the choice
The deciding question is whether the workflow has judgment.
If the work is “do A, then B, then C, no exceptions,” you want a workflow tool. n8n’s graph stays readable, debugging is straightforward (the data at each node is inspectable), and execution costs are predictable. Adding AI is a node, not a paradigm shift.
If the work is “decide what to do based on the inbound situation,” you want an agent. Lindy is built around this: the agent reads the trigger, considers its tools, and acts. The trade is observability — agent decisions can be opaque, and debugging “why did it skip the follow-up?” is harder than tracing a workflow graph.
A second deciding question is data sovereignty. n8n’s self-host path is the strongest in this comparison; Lindy is hosted-only. For internal-only data or regulated workloads, n8n self-hosted is often the only option that passes review.
Pricing model
The pricing models reflect the abstraction difference.
Lindy — per task
Lindy charges per task, where a task is one agent invocation that completes a goal. Tier-based plans include a monthly task allowance, with overages billed per task. The mental model is “tasks per month,” not “executions per month.”
For judgment-heavy work where each task replaces meaningful human time (15-minute lead qualification, 5-minute calendar scheduling), the per-task economics work — one task can be worth $5–$50 of replaced human time.
Live pricing: Lindy tracker.
n8n — per execution or self-host
n8n Cloud bills per workflow execution (multi-step executions counted as one billable unit), with a flat monthly tier and execution allowance. Self-hosted Community Edition is free under the AGPL — you operate the runtime, but execution count is unbounded.
For high-volume workflows (hourly cron, webhook-triggered flows that fire frequently), n8n self-hosted is dramatically cheaper than per-task pricing. For low-volume but high-judgment work, Lindy’s per-task model can be more reasonable per unit of value delivered.
Live pricing: n8n tracker.
Observability and debugging
This is where the platforms diverge sharply.
- n8n gives you a per-node inspector: at any point in the graph, you can see the data going in and the data coming out. Re-running from a specific node is one click. Workflow history is a flat log of executions with status.
- Lindy gives you per-task transcripts: the agent’s decisions, tool calls, and outputs are visible per task, but the model’s reasoning is partially opaque. You see what the agent did, not always why it chose that path over another.
For predictable workflows, n8n’s observability is faster to debug. For agent work, Lindy’s transcript view is the right primitive — but you trade some transparency for the agent’s autonomy.
Tool integration
Both have meaningful integration catalogs, but with different shapes.
- Lindy integrates with the tools an agent typically needs: Gmail, Outlook, Google Calendar, Slack, HubSpot, Salesforce, Notion, plus HTTP/webhook for custom services. The catalog is curated for agent use cases (read this, write that, schedule, search).
- n8n ships several hundred integration nodes covering core SaaS, dev tools, AI providers, and a generic HTTP node. Custom community nodes can be installed on self-hosted instances.
For typical agent workloads (inbox, calendar, CRM, comms), Lindy’s catalog is sufficient. For automation that touches the full surface area of a business (Stripe, Shopify, Linear, Notion, Slack, custom APIs), n8n’s catalog is broader.
Where each platform fits
Pick Lindy if:
- The work is judgment-heavy: qualify, summarize, draft, decide.
- Each unit of work replaces meaningful human time.
- You’re comfortable with hosted-only deployment.
- You want the platform to handle agent orchestration, not compose it yourself.
Pick n8n if:
- The workflow is deterministic and you want explicit step-by-step control.
- You need self-hosting for data residency or compliance.
- You expect high execution volume and want to avoid per-execution pricing growth.
- You want a visual graph that non-coders can read and modify.
Coexistence
Most builder stacks that use both put n8n at the orchestration layer (triggered by webhooks, cron, app events) and Lindy at the judgment layer (called from n8n when an agent decision is needed). n8n moves data and runs deterministic steps; Lindy decides what to do when the answer isn’t fixed.
Concretely: n8n’s HTTP node calls Lindy’s API to launch a task, waits for the result via webhook callback, then continues the deterministic graph with the agent’s output. Each tool plays to its strength.
Verdict
For builders in 2026 with judgment-heavy work (sales ops, inbox triage, content review), Lindy is the sharper tool. The goal-driven model removes the burden of composing chains, and the per-task economics align with the value delivered.
For builders with deterministic workflows at meaningful scale, n8n is the durable choice. The self-host path is unmatched in this comparison, and the visual graph + first-class code blocks make it suitable for everything from simple cron jobs to complex AI pipelines.
Most non-trivial automation surfaces benefit from both — n8n for the graph, Lindy for the agent calls. They aren’t direct substitutes.