n8n vs Lindy vs Relevance AI vs Dify vs Sierra: How to Choose an AI Agent Platform

"Agent platform" is a wide enough label that n8n, Lindy, Relevance AI, Dify and Sierra all fit under it — and buyers researching the category often assume they're picking between flavors of the same tool. They aren't. Read their own researched listings side by side and the real split isn't features, it's who's meant to build on the platform and how much control they get in exchange for that work. n8n and Dify are open-source, self-hostable developer tools: you get the source, you can run it on your own infrastructure, and building an agent means wiring a visual canvas (or code) yourself. Lindy and Relevance AI are closed-source, cloud-only SaaS: you describe what you want in plain language and the vendor runs it for you, with no self-host option at any price. Sierra sits outside that line altogether: a fully-managed, sales-led enterprise platform for one job — customer support and experience agents — with no public sign-up at any tier. Which side of the build-it-yourself line you want to be on, and whether you even want that choice, settles most of the shortlist before a single feature comparison matters.

The five, at a glance

Every figure below is pulled from each tool's own researched listing, last verified 13–21 July 2026; n8n's, Lindy's and Dify's pricing were re-checked live before publishing (Relevance AI's public pricing page now surfaces only its Enterprise tier — see the note below the table). Sierra publishes no self-serve pricing at all — see its own row.

Platform	What it actually is	Pricing	Open-source / self-hostable?	Known for
n8n	Visual workflow-automation platform with native AI-agent nodes and 400+ app integrations	Free (Community, self-hosted) → €20/mo (Cloud Starter) → €50/mo (Pro) → €667/mo (Business) → custom Enterprise	Yes — fair-code, source-available, Docker self-host	Widest integration library of the five; canvas can get unwieldy on deeply-branching agent logic
Lindy	No-code builder for event-triggered AI "employees" that automate recurring email, meeting and CRM work	No permanent free plan (7-day trial) → $49.99/mo (Plus) → $99.99/mo (Pro) → $199.99/mo (Max) → custom Enterprise	No — closed-source, cloud-only	The fastest, friendliest on-ramp to a working "AI employee"; credit-metered usage makes cost hard to predict
Relevance AI	No-code builder for coordinated multi-agent "workforces," with production infrastructure (evals, tracing, RBAC/SSO)	Free self-serve tier → self-serve Pro/Team tiers (published from $19–$234/mo) → custom Enterprise — though the public pricing page today foregrounds Enterprise contact-sales over the self-serve tiers	No — closed-source, cloud-only	Real production controls (LLM router, evals, RBAC/SSO) for multi-agent teams; dual-meter pricing (Actions + Vendor Credits) is easy to misjudge
Dify	Open-source visual platform for production LLM apps and agents, with a built-in RAG pipeline	Free (Community Edition, self-hosted) → free Sandbox (Cloud) → $590/yr (Professional) → $1,590/yr (Team) → custom Enterprise	Yes — Apache-2.0-derived (extra conditions), Docker self-host	All-in-one: workflow, RAG, agents, model management and observability in one open-source tool
Sierra	Fully-managed enterprise platform that builds and operates branded customer-support agents on your behalf	Outcome-based, custom-negotiated only — you pay per resolved issue; no public pricing, no free tier, escalations to a human are free	No — closed-source, no self-host; even the Agent SDK is gated to contracted customers	End-to-end action-taking support agents (refunds, subscription changes) with $150M+ ARR and customers like SoFi, Ramp and Chime

The decision: which side of the build-it-yourself line are you on?

All five carry a full researched verdict on their own listing, including who each one is explicitly not for. Read together, the honest decision tree runs on control versus convenience first, then on whether you even want a general-purpose builder at all:

• You want to build agentic automation visually, keep data on your own infrastructure, and connect to hundreds of existing apps → n8n. Its 400+ integrations and native AI-agent nodes mean an agent can actually go do something — call an API, update a CRM, post to Slack — and the Community edition is free to self-host. Watch out for: the fair-code licence is source-available, not OSI-approved open-source, so check the terms before reselling a self-hosted deployment commercially, and deeply branching agent logic can get hard to read on a visual canvas.
• You want a working "AI employee" running your inbox, meetings and CRM busywork today, and you don't want to touch code or infrastructure → Lindy. Event-driven agents act on real triggers — a new email, a booked meeting — and human-in-the-loop review keeps you in control while you get comfortable. Watch out for: usage is metered in credits with a recurring theme of billing surprises in independent reviews, there's no permanent free plan, and it's closed-source and cloud-only with no self-host option at any price.
• You want to run coordinated teams of agents in production, with the evals, tracing and access controls that separate a demo from something you'd trust with live pipeline → Relevance AI. Its LLM router picks the cheapest model that still passes your quality bars, and bring-your-own-keys keeps AI spend predictable. Watch out for: the dual meter of Actions plus Vendor Credits is easy to misjudge on AI-heavy agents, the flagship Bosh BDR agent isn't self-serve, and the public pricing page now leads with "talk to sales" over its own published self-serve tiers.
• You want an open-source, self-hostable platform that folds workflow, RAG and agents into one tool, and you have the technical chops to run it → Dify. A built-in RAG pipeline plus a model-agnostic runtime (hundreds of LLMs, swappable per node) cover prototype to production without stitching five tools together. Watch out for: the licence carries extra conditions beyond pure Apache-2.0 worth checking before commercial resale, self-hosting means you own the ops burden, and the managed cloud meters usage in message credits that heavier apps will outgrow.
• You don't want to build anything yourself — you want a vendor to design, run and improve branded customer-support agents for you, and you can commit to an enterprise engagement → Sierra. It resolves real customer issues end to end across every channel and prices on outcomes, not seats or credits. Watch out for: there is no public pricing, no free tier and no self-serve sign-up at any size, the developer-facing Agent SDK is gated to contracted customers, and it is overkill (and inaccessible) for anyone not buying a full enterprise engagement.

Lindy vs Relevance AI: the closest real head-to-head

Of the four general-purpose builders, Lindy and Relevance AI are the actual rivals — both are no-code, closed-source, cloud-only platforms selling "AI workforce" automation to non-developers, with no self-host option at any price. The difference is maturity and audience. Lindy optimizes for speed to a first working agent: describe an "employee" in plain language, wire a trigger and some of its 100+ integrations, and it's running your inbox or meeting notes within an afternoon — but it has no public API, so it's a closed box even for teams that outgrow the visual builder. Relevance AI optimizes for running many coordinated agents in production: it ships an LLM router, an evals framework, tracing and RBAC/SSO that Lindy doesn't offer, plus a real API and 2,000+ integrations via MCP — but that power comes with a steeper learning curve and a harder-to-predict dual-meter pricing model (Actions plus Vendor Credits, versus Lindy's simpler flat-tier-plus-credits). Pick Lindy if you want one or two agents running fast with the least setup; pick Relevance AI if you're building toward a fleet of agents that need to be monitored, evaluated and governed like production software.

Sierra: a fifth shape entirely, not a rival to the other four

Sierra is dual-listed in this category because it genuinely is an agent platform — Agent Studio for building agents, Ghostwriter for turning SOPs into working agents, and a gated Agent SDK for developers — but it doesn't compete for the same buyer as n8n, Lindy, Relevance AI or Dify. Those four are horizontal: you can build a support bot, a sales assistant or an internal ops agent on any of them. Sierra is vertical and single-purpose: it only builds and operates customer-support and customer-experience agents, and it does so as a fully-managed service rather than a product you sign up for. There is no free tier, no published self-serve pricing and no public API access — even the Agent SDK is gated to customers who've signed an enterprise contract. In exchange, Sierra brings a level of enterprise proof none of the other four claim: $150M+ reported ARR by February 2026, named customers including SoFi, Ramp and Chime, and $1.585B raised across four rounds (most recently $950M in May 2026 at a $15B+ valuation). If you need a general-purpose platform to build agents for any job, compare n8n, Lindy, Relevance AI and Dify above. If the job is specifically outsourcing customer support to a managed AI agent and you're an enterprise buyer who can run a sales engagement, Sierra is a different, narrower shortlist — see the AI customer-support agent guide for how it stacks up against Decagon, Intercom Fin, Crescendo and Cresta on that specific job.

One pattern the four builders confirm (and where Sierra breaks it)

n8n, Lindy, Relevance AI and Dify don't split on capability — all four can wire an LLM to a set of tools and integrations and let it act. They split cleanly on licensing philosophy, and that split predicts almost everything else about them. n8n and Dify are open-source at the core (n8n: fair-code/source-available; Dify: Apache-2.0-derived with extra conditions), both Docker-self-hostable, and both aimed at technical teams willing to own infrastructure in exchange for data control and no lock-in. Lindy and Relevance AI are closed-source SaaS with zero self-host option at any tier, and both are aimed at teams that would rather pay a vendor to run the infrastructure than manage it themselves. That split even shows up in API access: n8n, Relevance AI and Dify all ship a real API or MCP surface for programmatic use, while Lindy — despite selling to the same "AI workforce" buyer as Relevance AI — has none, a real gap for any team that outgrows its visual builder. Sierra breaks the pattern rather than extending it: it isn't open-source, but it also isn't self-serve SaaS — there's no tier at any price you can simply sign up for, closed or open. It's the one platform here you don't "choose" off a pricing page at all; you enter a sales process. There's no wrong side of the builder line; it's a genuine tradeoff between control and convenience, and it's worth deciding which side you're on — and whether you want a builder at all — before comparing feature lists.

FAQ

Which of these can I self-host?

n8n and Dify both offer a free, self-hostable Community/Docker edition. Lindy and Relevance AI are closed-source, cloud-only SaaS with no self-host option at any price. Sierra is also closed-source and cloud-only, delivered as a managed enterprise engagement rather than software you run yourself.

Which is easiest for a non-technical team to start with?

Lindy — you describe an agent in plain language and get a working "AI employee" running in an afternoon, with human-in-the-loop review by default. n8n and Dify assume more technical comfort with a visual canvas (or code); Relevance AI's production controls (evals, tracing, RBAC) add a real learning curve; Sierra isn't self-serve at all — onboarding is a sales-led enterprise engagement regardless of technical skill.

Which is built for running many agents together, not just one bot?

Relevance AI is purpose-built for multi-agent "workforces," with an LLM router, evals, tracing and RBAC/SSO for production use. n8n and Dify can chain multiple agent/workflow steps too, but neither ships the same dedicated multi-agent orchestration and governance layer.

Do any of these have a genuinely free, real open-source licence?

Neither n8n nor Dify is pure OSI-approved open source: n8n's Community edition is "fair-code" (source-available, free to self-host, but check the licence before commercial resale), and Dify's licence is Apache-2.0-derived with extra conditions on multi-tenant use and branding. Both are still free to self-host for internal use. Lindy, Relevance AI and Sierra are all closed-source.

Which has a public API?

n8n, Relevance AI and Dify all offer a real API (or MCP-compatible tool surface). Lindy has none — only its visual no-code builder. Sierra has a developer-facing Agent SDK, but it's gated to contracted enterprise customers rather than publicly available.

Is Sierra really an "agent platform," or should it be compared to customer-support tools instead?

Both, honestly — that's why it's dual-listed. Sierra ships real platform infrastructure (Agent Studio, an SDK, a supervision/analytics layer), which is why it belongs on this page. But its actual job — resolving customer support conversations end to end — puts it in direct competition with Decagon, Intercom Fin, Crescendo and Cresta, not with the four general-purpose builders on this page. If your job is "build an agent for X," compare n8n, Lindy, Relevance AI and Dify. If your job is specifically "outsource customer support to an AI agent," start with the customer-support agent guide instead.

Every platform above carries its own full researched listing — pricing tiers, sourced pros and cons, and a committed verdict on who it's for and who it isn't. Start with the agent platforms category for the full set.