Current facts
Confirm the vendor source
Check pricing, packaging, security docs, support limits, AI feature availability, and contract terms directly with the vendor.
Compare = pick the system around the number
Agents or n8n?
Decide
n8n is a source-available, self-hostable workflow platform that technical teams genuinely like — a node-based canvas, real code steps, 400+ integrations, and 70+ LangChain nodes, so it can run AI agents itself. That makes this less "automation vs AI" and more a question of ownership: a stack you build and maintain in-house, or a governed agent system built and run for you.
Quick verdict
Choose a custom AI agent system when you want the judgment, evals, and observability built in and delivered done-for-you, without standing up an in-house team to build and maintain the stack. Choose n8n when you have technical people who want to self-host, control the stack, and build (and run) automations and agents in-house on a node-based canvas. n8n can run AI agents itself, so the real question is not whether it does AI (it does), it is who builds the judgment layer, who governs it, and who keeps it running.
Side by side
AI Agents vs n8n at a glance
The dimensions that matter when the stack has to support qualified leads, fast follow-up, clearer pipeline, or better conversion.
| Dimension | AI Agents | n8n |
|---|---|---|
| What it is | A purpose-built agent system, built and governed for one job, delivered done-for-you. | A self-hosted, node-based automation platform with 400+ integrations that can also run LangChain-based AI agents on its canvas. |
| Who builds and runs it | Built, evaluated, and maintained by an outside team. You own the outcome, not the upkeep. | You build and run it. Strong for technical teams, but you supply the developers and the ongoing maintenance. |
| AI agent support | The agent is the whole system: a judgment loop, tools, and guardrails designed around your workflow. | Ships 70+ LangChain-based AI nodes and an AI Agent node, so n8n can orchestrate agents inside the canvas. Verify the current nodes on n8n.io. |
| Hosting & data control | Runs where you deploy it. Hosting and data residency are part of the build plan. | Self-hostable in your own VPC on the free Community Edition, so data never leaves your infrastructure. A real strength for regulated teams. |
| Evals, observability & governance | Evals, tracing, guardrails, and human review gates are built in from day one. | Inline execution logs plus a newer Evaluations feature (still maturing). Plan trails, rollback, and access control land on you or the Enterprise tier. |
| Pricing shape | Fixed, named build plan plus ongoing inference and maintenance. | Free self-hosted Community Edition with unlimited executions; cloud tiers bill per workflow execution, and SSO and version control sit on paid tiers. Verify current pricing on n8n.io. |
| Time to value | Weeks. Discovery, build, evals, deployment, and handoff. | Fast for a first workflow. A governed, production-grade agent still takes real engineering time to build and harden. |
| Best fit | Teams that want the judgment, eval, and observability layer and the outcome, without hiring an AI build team. | Technical teams that want to self-host, control the stack, and build plus maintain automations (and agents) in-house. |
Vendor pricing and feature claims change frequently. Verify details directly with each platform before committing.
Verify before buying
Check the facts that change fast
Comparison pages are useful only when the buyer knows what to verify. Use this section as the buying checklist before trusting any vendor page, review article, or sales deck.
What changes often
Features and limits move
AI features, usage caps, add-ons, integration limits, and support tiers can change faster than a comparison page can stay current.
Workflow decision
Map your own work
The right answer depends on the repeat workflow, source data, owner, review step, integration needs, and measurable business result.
Choose AI Agents
When this path fits
- The value is in the judgment layer — reading intent, deciding the next move, drafting — and you want that governed.
- You want evals, tracing, and human review gates built in, not bolted on after something breaks.
- You do not have, or do not want to tie up, an in-house team to build and maintain the stack.
- The workflow matters enough to justify a purpose-built system with someone accountable for the outcome.
- You want the result shipped and kept running, not a canvas to learn.
Choose n8n
When this path fits
- You have technical people who want to self-host and keep data inside your own infrastructure.
- You want to own and control the stack, with real code steps (JavaScript on any instance, Python when self-hosted).
- The automations are well understood and your team is happy to build and maintain them.
- You are wiring many of the 400+ integrations together and want one canvas for it.
- You want to prototype agents in-house with the LangChain nodes before committing to a bigger build.
How we would actually decide
The platform is only useful if the system moves revenue
n8n is a good tool, and we are not here to talk you out of it. For a technical team that wants to self-host, keep data in its own VPC, and own the stack, a node-based canvas with real code steps and 70+ LangChain nodes is a strong place to build. Graded on its own terms, it earns the following it has.
But "n8n can run agents" and "you have a governed agent in production" are two different sentences. The canvas gives you the wiring. It does not give you the judgment about which workflow is worth building, the evals that tell you the agent is right often enough to trust, the observability to catch drift, or the person accountable when it is wrong at 2am. Those are the parts that decide whether an agent makes money or quietly makes mistakes, and a platform leaves them to you.
So the honest split is about who owns the hard part. If you have the engineers and want to build and run it yourself, n8n is a real answer. If you want the judgment, evals, and observability built in, and the thing delivered and maintained without hiring an AI team, that is a custom build. Most teams we meet do not lack a tool, they lack the layer that makes the tool trustworthy.
We do not start with the canvas. We start with the workflow that is losing money, decide whether an agent is even the right fix, then build the smallest governed system that moves the number. If you want that read on your own stack before you commit to building or buying, start with a free AI System Plan.
Frequently asked
AI Agents vs n8n questions answered
Can n8n build AI agents, or just automations?
Both. n8n ships 70+ LangChain-based AI nodes and an AI Agent node, so it can orchestrate LLM agents on its canvas, not just move data between apps. The open question is not whether n8n does AI — it clearly does. It is whether you have the team to build, evaluate, and maintain a production agent, and the governance to trust it in front of customers. Verify the current node set on n8n.io.
Is n8n really free?
The self-hosted Community Edition is free with unlimited executions, which is a real strength if you have people to run it. n8n Cloud bills per workflow execution (one run counts once, regardless of steps) across paid tiers, and some governance features like SSO and version control sit on the Business or Enterprise license. The cost that never shows on the pricing page is the engineering time to set up, secure, and maintain a self-hosted instance. Always verify current pricing on n8n.io.
If n8n can host agents, why pay for a custom build?
Because the platform is the easy part. The hard part is deciding which workflow is worth automating, writing evals so you can trust the agent, adding observability to catch drift, and keeping it running as your data and models change. n8n gives you the canvas and leaves those to you, which is the right trade if you have engineers. A custom build delivers the judgment and governance layer, plus the outcome, without you standing up and staffing an AI team.
Who is n8n actually best for?
Technical teams that want to self-host, keep data inside their own infrastructure, and own the stack. The Code node runs JavaScript on every instance and Python when self-hosted, so developers get code as a first-class step alongside the visual nodes. If you have that team and want control, n8n is a strong pick. If you want the result without owning the build-and-maintain burden, it is the wrong lever — and that is not a knock on the tool.
Can we start on n8n and move to a custom build later?
Yes, and it is often the sensible path. Use n8n to prototype the workflow and prove an agent is worth building, then harden the parts that matter with evals, observability, and human review gates. Nothing is wasted — the prototype tells you exactly what the governed build has to do. A free AI System Plan tells you which stage you are at.
How do I decide between n8n and a custom agent build?
Answer two questions. (1) Do you have technical people who want to own and maintain the stack, or do you want the outcome delivered and kept running? (2) Does this workflow need real evals and governance because a wrong answer reaches a customer or costs money? If you have the team and the risk is low, self-host on n8n. If the risk is real and you would rather not staff it, a custom build is the safer call. If you want a no-pitch second opinion, contact us.
More comparisons
Other decisions worth getting right
Compare
HubSpot vs GoHighLevel
HubSpot wins on data depth and reporting, GoHighLevel on agency speed and white-label. How to pick for AI marketing workflows.
Compare
AI Agents vs Zapier
Zapier connects apps with rules. AI agents reason and decide. Choosing between deterministic automation and autonomous workflows.
Compare
Custom AI vs ChatGPT
ChatGPT is fast and general. Custom AI is slower, defensible, and yours. Which one moves the revenue needle for your business.
Compare
Agency vs In-House
Hire an agency for speed, fixed cost, and depth without hiring risk. Build in-house when AI is core and the volume is steady.
Compare
AI Agents vs Make
Make runs apps with visual no-code scenarios. AI agents reason and decide. When to use bounded automation, open judgment, or both.
Compare
Custom AI vs Jasper
Jasper writes fast, on-brand content. Custom AI is a system wired to your data and buyer path. Content problem or system problem?
Compare
Custom AI vs HubSpot
HubSpot Breeze is the low-friction pick when HubSpot is your system of record. Custom AI wins when the work spans tools HubSpot does not own.
Compare
AI Agents vs Agentforce
Agentforce is the pick for Salesforce-native orgs with clean Data Cloud data. Custom AI wins when the work crosses the Salesforce wall.
Compare
Custom AI vs Copilot
Microsoft Copilot is the low-friction pick for Microsoft 365 shops. Custom AI wins when the work crosses out of Microsoft or you want it delivered.
Compare
AI Agents vs Lindy
Lindy is the fast, self-serve pick for standard SMB automations. Custom AI wins when the workflow needs judgment, evals, and an owner.
Compare
AI Agents vs Relevance AI
Relevance AI fits teams that want to build an agent workforce themselves. Custom AI fits when you want the governed outcome delivered for you.
Next step
Turn the comparison into a revenue decision
If the wrong stack is slowing response speed, qualification, handoff, or reporting, the AI System Plan tells us whether a build should exist.