Lindy vs n8n: Which automation platform for AI agents?

Lindy if ops teams need to ship agents this quarter without engineering; n8n if engineers want a self-hosted workflow engine with AI as one node among many.

Lindy and n8n both let teams build AI agents without writing application code, but they make opposite trade-offs on flexibility versus accessibility. The decision usually comes down to who’s building.

TL;DR

Lindy is a no-code agent builder optimized for non-technical B2B operators — sales ops, RevOps, marketing automation, customer success teams. n8n is an open-source workflow engine optimized for engineering-capable teams who want self-hosting, flexibility, and AI as one node in a broader automation stack.

Lindy if the builder is in ops, sales, marketing, or success — and engineering bandwidth is the constraint
n8n if engineering owns automation, you want self-hosting, and AI agents are part of a broader workflow story

These aren’t substitutes. Many production stacks run both: Lindy on the front-line B2B automations (inbox triage, CRM updates, meeting prep), n8n on the deeper data and orchestration workflows behind them.

At a glance

Dimension	Lindy	n8n
Primary audience	Ops, sales, marketing	Engineering / DevOps
Pricing model	$49-$499/month tiers	Free self-host or $20-$50+/month Cloud
Self-host	No	Yes (Sustainable Use License)
Builder paradigm	Agent with goals + tools	Workflow with triggers + nodes
Native integrations	100+ B2B-focused	400+ general-purpose
AI agent native?	First-class	Via dedicated AI node
Code escape hatch	Limited	JavaScript + Python nodes
Observability	Functional	Excellent per-execution
Time to first agent	Hours	Days

Use case framing

The decisive question: who’s building the automation, and what’s the broader stack?

Sales/RevOps/marketing-led automation. Lead qualification on inbound forms. Meeting prep for AEs. CRM enrichment from public sources. Outbound personalization at scale. Customer success follow-ups. These use cases have shared shape: an event triggers an agent that uses CRM and email tools to do specific knowledge work. → Lindy is purpose-built for this. The templates match, the integrations are deep, the mental model matches the operator’s job.

General automation across the organization. Customer data flowing between SaaS tools. ETL-style data pipelines with AI enrichment in the middle. Multi-system orchestration where AI is one capability among many. Cross-team workflows that span engineering, sales, and operations. → n8n is the right tool. Workflow engines handle this; agent platforms struggle with it.

Mixed needs. Most growing B2B organizations have both. The pragmatic stack: Lindy for the B2B-shaped agent work close to CRM and inbox, n8n for the cross-system orchestration that sits behind it. Lindy can trigger n8n workflows as HTTP webhook endpoints; n8n can call Lindy agents the same way. They compose cleanly.

Feature deep-dive

Builder experience. Lindy’s visual builder treats agents as first-class — you define a goal, pick tools, write prompts in plain language. n8n’s builder treats workflows as first-class — you define triggers, chain nodes, route data. For an ops user building “an agent that handles inbound leads,” Lindy’s mental model fits the task. For an engineer building “a workflow that ingests data, calls AI for enrichment, writes to multiple destinations,” n8n’s mental model fits.

Integration depth vs breadth. Lindy has roughly 100+ native connectors with deep integration on the B2B-critical ones: HubSpot, Salesforce, Outlook, Gmail, Slack, Calendly, Linear, Notion. The HubSpot integration in particular is the deepest of any agent platform in 2026. n8n has 400+ official and community nodes spanning a much wider range of systems, but the integrations are shallower per system — usually CRUD operations rather than tuned-for-the-use-case actions.

AI agent node (n8n). n8n’s dedicated AI Agent node is genuinely capable: LLM with tool list, ReAct loop, memory, configurable everything. It’s powered by LangChain under the hood, which means it inherits LangChain’s strengths (broad tool ecosystem) and weaknesses (more configuration than non-technical users want). You can build sophisticated agents in n8n, but you build them — you’re not assembling from pre-tuned components.

Multi-agent / orchestration. Neither is ideal for multi-agent setups (CrewAI is). Lindy supports basic agent-to-agent handoffs; n8n can run multiple AI nodes in sequence with shared context. For real multi-agent collaboration, both fall short — and you’d reach for CrewAI or LangGraph instead.

Code escape hatch. n8n’s JavaScript and Python code nodes let engineers handle edge cases without leaving the platform. Lindy’s code capability is much more limited — you can call custom HTTP endpoints but you can’t easily execute arbitrary code in the workflow. For engineering teams hitting edge cases, n8n’s escape hatch is meaningful.

Self-hosting. n8n’s Docker-compose deployment is genuinely simple for any DevOps-capable team. Sustainable Use License permits self-hosting for internal use without restriction. Lindy has no self-host option — fully cloud-based.

Pricing comparison

Lindy is subscription-priced:

Starter $49/month: 400 tasks
Pro $199/month: 10,000 tasks
Business $499/month: 50,000 tasks
Enterprise: contract-priced

Per-task economics: roughly $0.12 (Starter) → $0.02 (Pro) → $0.01 (Business). Predictable, flat-fee structure.

n8n self-hosted: ~€20/month for a small VPS plus LLM token costs. Scales linearly with infrastructure, not usage. The labor cost (DevOps time) is the hidden line.

n8n Cloud: $20/month (Starter, 2,500 executions); $50/month (Pro, 10,000 executions); higher tiers up to $480+/month.

At 1,000 tasks/month: Lindy Pro ($199) vs n8n Cloud Starter ($20) — n8n is 10x cheaper, but the platform also requires more configuration time.

At 10,000 tasks/month: Lindy Pro ($199) vs n8n Cloud Pro ($50) or self-hosted (~€50 all-in) — n8n is 4-10x cheaper.

At 100,000+ tasks/month: Lindy Business ($499) vs n8n self-hosted (~€100-200 infra) — n8n is 3-5x cheaper. Above this scale, both platforms push into custom Enterprise pricing.

The cost comparison misleads if taken alone. Lindy’s premium pays for the templates, the integration depth, and the on-ramp — value that non-technical teams can’t extract from n8n at any price. n8n’s lower cost reflects that the platform is BYO-everything for non-technical users.

When to pick Lindy

Your builders are in ops, sales, marketing, or success — not engineering
Your first use cases live in the HubSpot / Outlook / Slack / Salesforce world
You need to ship 3-10 agents this quarter without engineering involvement
Predictable subscription pricing matters more than per-task optimization
The work decomposes into single-agent automations with B2B-shaped integrations

When to pick n8n

Engineering owns the automation stack
Self-hosting is a real benefit (data residency, cost, regulatory)
Use cases span the whole organization, not just B2B revenue functions
You need code escape hatches for complex edge cases
AI agents are one capability in a broader workflow story, not the headline

Verdict

Lindy and n8n succeed at adjacent but different problems. Lindy is the right default for ops-led B2B agent work; n8n is the right default for engineering-led general automation with AI capabilities. Trying to use Lindy for cross-system orchestration produces brittle workflows; trying to use n8n for ops-driven CRM agents produces unfinished products that ops users can’t maintain.

If you can only afford one platform, pick the one that matches your team’s center of gravity — not the one that’s marketed to your industry. If your roadmap genuinely needs both shapes of automation, run both. The integration cost is low (HTTP webhooks both ways) and the conceptual cost is real but worthwhile. See FAQ below.

FAQ

Is n8n really cheaper than Lindy? +

At scale, yes — by a wide margin. n8n self-hosted on a $20/month VPS plus LLM tokens beats Lindy's tier pricing by 5-20x at high volume. The catch: someone needs to operate the VPS, manage upgrades, handle backups, and debug failures. For non-technical teams, that cost difference doesn't matter because they can't realistically self-host.
Can Lindy do what n8n does? +

Partially. Lindy handles single-agent automations with deep CRM/email integration extremely well. n8n handles general-purpose workflows — ETL-style data movement, complex branching, multi-system orchestration — with much more flexibility. They overlap on the simple cases; they diverge on the complex ones.
Can n8n do what Lindy does? +

Yes, technically — you can build inbox-triage agents or CRM enrichment agents in n8n. But you'd be rebuilding what Lindy ships pre-tuned. n8n's AI node is functional but you do the orchestration work yourself; Lindy's agent builder is opinionated about how B2B agents should work and that opinion is usually right.
What about n8n Cloud — does it match Lindy's UX? +

n8n Cloud removes the self-hosting burden but keeps the workflow-engine paradigm. Cloud users still think in terms of triggers → workflow steps → actions, not in terms of agents with goals and tools. For ops teams, Lindy's mental model is more accessible regardless of where n8n is hosted.

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