Lindy vs n8n (2026): AI Employee or Workflow Engine

Lindy hires; n8n builds. That’s the whole split. Lindy sells a teammate: since the August 2026 relaunch, one Slack-native AI employee that anyone on the team hands work to in plain English — inbox triage, meeting follow-up, CRM updates — and that keeps company context from the channels and calls around it. n8n sells a visual canvas where you wire the logic yourself, node by node, with code escape hatches when the visual builder runs out of road. Both now do serious AI-agent work; they disagree about who should assemble it.

The pricing models are the real difference

Lindy bills per credit, per active user. As of October 2026 there is one paid plan: Team at $49.99/mo per active user for 5,000 credits, pooled across the workspace. Need more, and you buy a bigger credit tier per seat ($99.99 for 15,000, $199.99 for 35,000) or top up at $10 per 1,000 credits. Model selection is included; the ladder is usage headroom, not features. No annual option is listed, and monthly credits don’t roll over. The free start is $50 in credits, no card, good for 7 days.

n8n bills per execution (cloud) or nothing at all (self-hosted Community, unlimited). A workflow with 50 steps costs the same as one with 2 — complexity is free, you pay in setup time instead. Cloud Starter runs 20€/mo annual for 2,500 executions; Pro is 50€/mo for 10,000. Both include AI credits for the agent-builder features on top of the execution quota.

The shape of the bill tells you what you’re buying: Lindy charges for the agent doing the work, n8n charges for the work itself.

Where Lindy wins

• Time to staffed. Add it to Slack, describe the job, approve the first few runs. No workflow to design.
• Delegation framing. You ask Lindy in Slack to “run the handoff,” not wire a sequence of eleven trigger-action steps — closer to how delegation actually works.
• One plan, sized by credits. Every paid seat gets model selection and the full Slack teammate; you scale by buying credits, not by unlocking features.
• iMessage, meetings, daily briefs. Built-in surfaces n8n doesn’t try to compete on.

Where n8n wins

• Cost at volume. A workload that burns through Lindy’s credit pool in a week runs for the price of a small VPS on self-hosted n8n.
• Real branching logic. Loops, conditionals, error handling, and JavaScript/Python nodes when the job needs actual programming, not a role description.
• Trust boundary. Self-hosted means client data never leaves infrastructure you control — Lindy’s agents run on Lindy’s servers.
• Connector depth for engineered workflows. HTTP nodes and a mature AI Agent node (structured tool calling, four memory backends, human-in-the-loop gates) make n8n the deeper agent-orchestration layer once you’re building rather than hiring.

The call

Situation	Pick
“I need someone to own my inbox this week”	Lindy
Non-technical founder, no time to learn a builder	Lindy
High-volume workflow, cost matters	n8n
Multi-step branching logic with real conditionals	n8n
Compliance-sensitive data that can’t transit a third party	n8n self-hosted

Every AI tool needs a job, not a folder. If the job is “be my assistant,” hire Lindy. If the job is “run this exact process, every time, at scale,” build it in n8n.