Agentic Index
n8n vs Relevance AI (2026)
Relevance AI suits sales, ops and support teams that want to build agents without developers, and n8n suits technical teams that want full control of the workflow and where it runs. That verdict is the Agentic Index coverage score, graded from each vendor's own published materials.
Relevance AI builds an agent from a plain language description, a marketplace clone or a blank start. Agents then link into a workforce on a canvas where each one owns a step and hands its context to the next, such as researching a prospect, drafting the outreach and reviewing its tone. n8n is a workflow automation platform where builders lay out triggers, branches and error handling node by node and drop into JavaScript or Python when drag and drop runs out. Memory separates them. Relevance AI agents keep long term memory across conversations through save and delete tools, while n8n's default agent memory lasts only for a session unless an outside store is attached. Hosting separates them too. Relevance AI is hosted only, in a US, EU or Australian region picked at signup that cannot be switched later without support, and n8n can run on the customer's own servers. The meters differ as well. Relevance AI counts every tool run as an Action and passes model costs through as Vendor Credits at provider rates, which a team skips by bringing its own model keys. n8n counts one execution per workflow run, however many steps it takes. Both score agents against test cases, though Relevance AI keeps its evaluations, along with single sign on and role based access, on the Enterprise plan while n8n ships evaluations as core nodes.
This comparison is published by Agentic Index, an independent agentic AI vendor research platform. n8n and Relevance AI are each graded against the same 14 capability Agentic Index taxonomy, from the vendor's own public materials under the Agentic Index verification standard, alongside 1,061 researched vendors. No vendor pays for placement and no vendor has reviewed this page. How this evidence is graded
Choose n8n if
- Engineers want to write code inside workflows and keep them under Git based controls.
- Automation has to run self hosted, air gapped if needed.
- Billing should count workflow executions, however many steps each one takes.
- Evaluation nodes should be available without an enterprise contract.
- A free Community Edition matters for a first rollout.
Choose Relevance AI if
- Sales, ops or support staff should build and run agents without a developer.
- Several agents should pass work along a chain, each owning one step.
- Agents should remember people and past conversations over the long term.
- A ready agent from a marketplace should be the starting point.
- Each agent should retry a failed task on a backup model from another provider.
| Feature | n n8n |
R Relevance AI |
|---|---|---|
| Action & orchestration | ||
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Integrations & Tool Calling Ability to connect agents to real systems through native integrations, OAuth-authenticated actions, custom tools, APIs, webhooks, or MCP-compatible tools. |
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n8nIntegrations & Tool Calling Several hundred built in app nodes span CRM, marketing, ITSM, HR, databases, warehouses, cloud infrastructure, storage, messaging, security and finance, and major nodes such as Gmail, Google Drive, Google Sheets, Postgres and OpenAI each cover several families of operations. Core nodes add HTTP Request, GraphQL, SSH, Execute Command and Code for anything not in the catalog, community and custom nodes extend the set further, and the MCP Client node connects agents to external MCP servers. Sub-workflows and app nodes can be exposed to agents as tools. Sourcedocs.n8n.io app nodes, core nodes, MCP Client and how tools work pagesread 2026-08-31 |
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Relevance AIIntegrations & Tool Calling Agents call tools built in a no code tool builder and connect to a catalog of more than 2,000 integrations, and an MCP client lets them use tools from outside MCP servers. Sourcerelevanceai.com/pricingread 2026-09-27 |
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Workflow Orchestration Ability to sequence, branch, retry, route, and combine deterministic workflow nodes with autonomous agent steps. |
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n8nWorkflow Orchestration n8n workflows split with If and Switch conditionals, merge data, loop, wait, handle errors gracefully and run workflows with several branches in a defined execution order. Workflows can call other workflows, and converting nodes to a sub-workflow automatically brings along attached AI sub-nodes such as chat models and memory. Agent nodes act as root nodes orchestrating typed sub-node connections for language models, tools, memory and output parsers, and sub-workflows can be attached to an agent as tools. Canvas groups, sticky notes and workflow tags help organize large workflows. Sourcedocs.n8n.io flow logic tree, break workflows into smaller parts, convert to sub-workflows and how tools work pagesread 2026-08-31 |
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Relevance AIWorkflow Orchestration Workforces connect several agents and tools on a canvas with conditions on the edges between them, agents can hand work to subagents, and the tool builder supports looping and branching steps. Sourcerelevanceai.com/docs/build/workforces/workforce-features/approvals-and-escalations.mdread 2026-09-27 |
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Triggers & Channel Coverage How agents wake up and where they work: schedules, webhooks, message events, CRM events, inbox events, chat, email, voice, and collaboration tools. |
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n8nTriggers & Channel Coverage Trigger nodes include Schedule Trigger, Webhook, Chat Trigger, Email Trigger over IMAP, RSS Feed Trigger, Local File Trigger, SSE Trigger, n8n Form Trigger, Error Trigger, Activation Trigger, Workflow Trigger, Execute Sub-workflow Trigger, n8n Trigger, Evaluation Trigger, MCP Server Trigger and Microsoft Agent 365 Trigger. On self hosted instances a durable scheduler runs time based workflows from a queue backed by the database. Agents can be published so people reach them through chat, channels and schedules, and a Respond to Webhook node plus streaming responses complete the request and response surface. Sourcedocs.n8n.io core node reference, durable scheduler, build and manage agents and stream real-time responses pagesread 2026-08-31 |
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Relevance AITriggers & Channel Coverage Scheduled triggers let an agent act on its own on a recurring schedule or send messages at set future times, and agents also start from integration events, custom webhooks, an API trigger and tools used as triggers. Sourcerelevanceai.com/docs/build/agents/build-your-agent/agent-triggers/scheduled-triggers.mdread 2026-09-27 |
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| Knowledge & context | ||
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Knowledge Grounding & RAG Ability to ground agent behavior in company data through document ingestion, retrieval, external knowledge APIs, semantic search, or RAG layers. |
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n8nKnowledge Grounding & RAG Data can be stored and searched with vectors through vector databases, embeddings, retrievers and document loaders, and retrieval augmented generation pulls relevant context into a workflow. Vector store providers attach as sub-nodes so the index can be held in a database the customer runs, and a worked example scrapes website content into Pinecone and queries it from a chat workflow. Data tables manage structured tabular data within project boundaries, and Default Data Loader and text splitter components handle ingestion. Sourcedocs.n8n.io store and search data with vectors, retrieve relevant context, use website content and data tables pagesread 2026-08-31 |
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Relevance AIKnowledge Grounding & RAG Knowledge sets are built from uploads (CSV, PDF, Excel, JSON, audio), website extraction, manual entry, and syncs from Google Drive, SharePoint and Notion, and an agent either takes the whole set in its prompt or searches it by retrieval with relevance thresholds. Sourcerelevanceai.com/docs/build/knowledge/create-knowledge.mdread 2026-09-27 |
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Memory & State Persistence Ability to persist context across a run, conversation, workflow, user, team, or longer-term memory layer. |
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n8nMemory & State Persistence A memory sub-node on the Tools Agent lets users hold an ongoing conversation across several queries, but that memory does not persist between sessions, and the default Simple Memory node, previously named Window Buffer Memory, is a bounded buffer. Memory attaches to agents as a typed AiMemory sub-node, with session IDs taken from input data or a custom key and optionally scoped per node so separate memory nodes in one workflow do not share history. External chat memory backends can be attached in place of the simple buffer, and Data tables provide structured storage across runs. Sourcedocs.n8n.io Tools Agent, how memory works, AI Agent common issues and data tables pagesread 2026-08-31 |
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Relevance AIMemory & State Persistence Long term memory lets an agent remember information across different conversations through save to memory and delete from memory tools, alongside short term memory that holds extracted fields for one conversation. Sourcerelevanceai.com/docs/build/agents/build-your-agent/memory.mdread 2026-09-27 |
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| Control & trust | ||
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Human Oversight & Guardrails Approval steps, consent checkpoints, escalation rules, structured guardrails, policy constraints, and pause/resume controls. |
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n8nHuman Oversight & Guardrails An AI Agent can be required to get a person's approval before it runs specific tools, and a human fallback brings in a person to answer when the AI cannot help. A dedicated Guardrails node ships as a core node for enforcing policy on AI workflows. Workflow reviews let a builder submit a version for review before publishing, compare changes in a visual diff, discuss them in activity comments, and approve or request changes. Wait and Stop And Error nodes pause and halt runs, and publishing a workflow is a separate step from saving it. Sourcedocs.n8n.io human-in-the-loop for tools, set a human fallback, Guardrails node, workflow reviews and save and publish pagesread 2026-08-31 |
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Relevance AIHuman Oversight & Guardrails Approval settings are configured per edge, so a sensitive tool can require approval while routine ones run automatically; in approval required mode the agent drafts its action and waits, and a reviewer approves, rejects or adds guidance from the task view. A let agent decide mode and escalations also exist. Sourcerelevanceai.com/docs/build/workforces/workforce-features/approvals-and-escalations.mdread 2026-09-27 |
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Security, Identity & Governance RBAC, SSO, auditability, encryption, least-privilege tool access, compliance posture, and data handling policy. |
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n8nSecurity, Identity & Governance An independent auditor evaluates n8n continuously and audits it each year against SOC 2. Its SOC 2 report is available to enterprise customers, a SOC 3 report is published for everyone else, and third party penetration tests of the production environment run at least once a year. SSO, SAML and LDAP come on the Enterprise plan and advanced RBAC on all paid plans. Security settings add SAML and OIDC single sign on, MFA enforcement, a self service security audit, node blocking, task runner hardening, SSRF protection, encryption key rotation, JWE decryption of OAuth tokens and execution data redaction. Sourcen8n.io legal security page, docs.n8n.io security configuration treeread 2026-09-29 |
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Relevance AISecurity, Identity & Governance Relevance AI offers role based access control, SSO and SAML, directory sync, audit logs, PII masking and encryption at rest, and states SOC 2 Type II compliance. SSO, RBAC and audit logs sit on the Enterprise plan. A trust center at trust.relevanceai.com carries the report list. Sourcerelevanceai.com/enterpriseread 2026-09-27 |
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Observability & Auditability Traces, logs, execution histories, metrics, audit events, and debugging detail for production agent behavior. |
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n8nObservability & Auditability Executions are first class objects. Teams can view all executions or those of a single workflow, add custom execution data so runs can be filtered by custom fields, and debug by copying earlier execution data into the canvas. Workflow and node executions can be traced to an OpenTelemetry collector, alongside Prometheus metrics, metrics visualized in Grafana, log configuration and an insights metrics layer. Workflow change history and version restore are available, execution data can be redacted for compliance, and a self hosted instance can connect to LangSmith for tracing through LangChain in n8n. Sourcedocs.n8n.io understand executions, trace executions with OpenTelemetry, monitor n8n, view change history and LangChain in n8n pagesread 2026-08-31 |
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Relevance AIObservability & Auditability Execution traces cover agent invocations, individual LLM calls, workforce runs and condition evaluations, and audit logs cover creation, publishing, deletion and permission changes; on the Enterprise plan both stream to the customer's S3 for OTEL backends. A tasks view shows every agent and workforce run with errors and pending approvals, and views of run cost and outcomes sit alongside it. Sourcerelevanceai.com/docs/enterprise/streaming-events.mdread 2026-09-27 |
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Deployment & Data Residency Deployment modes and options, including SaaS, dedicated cloud, VPC, on-prem, hybrid, local runtime, and self-hosting. |
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n8nDeployment & Data Residency n8n installs with a one line setup, Docker, Docker Compose or npm, and deploys to DigitalOcean, Heroku, Hetzner, AWS, Azure, Google Cloud Run, Google Kubernetes and OpenShift Local, alongside managed n8n Cloud. An isolated configuration keeps the instance from connecting with n8n's servers. The customer chooses the database, binary and execution data can go to external storage, queue mode and task runners cover scaling, and an OEM path puts n8n inside another product. Editions run from Community and Registered Community to Business and Enterprise. Sourcedocs.n8n.io install options, isolate n8n, choose n8n's database, scaling and compare editions pagesread 2026-08-31 |
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Relevance AIDeployment & Data Residency An organization picks its region at signup from three named regions, US (N. Virginia), EU (London) and AU (Sydney), and the region cannot be changed afterward without support. The service is hosted SaaS, and Relevance AI does not describe a self hosted or VPC option. Sourcerelevanceai.com/docs/admin/project-management/ids.mdread 2026-09-27 |
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| Solution readiness | ||
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Prebuilt Agents, Templates & Packs Ready-made workflows, packaged employees, templates, blueprints, industry solutions, and role-specific agents that reduce time-to-value. |
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n8nPrebuilt Agents, Templates & Packs Templates are one of the named ways to build workflows, and self hosted instances can point at a custom workflow templates library. A curated self hosted AI Starter Kit provides a set of AI elements for starting AI workflows quickly. Each node links to browsable template collections for that node, and .n8np packages bundle workflows, folders or whole projects with their dependencies into a portable file for moving between instances. Learning paths offer interactive courses that build real workflows. Sourcedocs.n8n.io use templates, configure a custom workflow templates library, deploy with the AI starter kit and n8n packages pagesread 2026-08-31 |
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Relevance AIPrebuilt Agents, Templates & Packs A marketplace carries agents and tools from Relevance staff and verified builders, free or paid, that can be cloned into a project and customized, alongside agent and tool templates and curated multi agent systems such as a BDR agent sold through sales. Sourcerelevanceai.com/docs/get-started/marketplace/introduction.mdread 2026-09-27 |
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| Platform extensibility | ||
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Model Flexibility & Routing Ability to work across multiple foundation models, route tasks to different models, or let buyers bring their own providers and keys. |
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n8nModel Flexibility & Routing The AI Agent node needs a connected Chat Model sub-node and errors without one, and clicking the Chat Model connector opens a selection of possible chat models. Models attach as sub-nodes, so different agents and chains in one workflow can use different models. Dedicated model provider nodes include OpenAI, Anthropic, Google Gemini, Mistral AI, Perplexity, Qwen Cloud, MiniMax and Moonshot Kimi, and the self hosted AI starter kit runs local models alongside n8n. LangChain is the underlying abstraction, with a LangSmith connection. Sourcedocs.n8n.io AI Agent node and common issues, what agents do, app node reference and AI starter kitread 2026-08-31 |
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Relevance AIModel Flexibility & Routing Each agent picks its model from several providers, including Anthropic Claude, OpenAI and Gemini, and can set a backup model, recommended from a different provider, that retries a failed task once. LLM integrations cover OpenAI, Gemini, Anthropic, Azure and OpenRouter. Sourcerelevanceai.com/docs/build/agents/build-your-agent/agent-settings/language-model.mdread 2026-09-27 |
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APIs, SDKs & MCP Extensibility Composability layer: stable APIs, SDKs, MCP tool consumption/serving, custom tools, and integration into internal systems. |
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n8nAPIs, SDKs & MCP Extensibility The MCP Server Trigger node lets n8n act as a Model Context Protocol server, making n8n tools and workflows available to MCP clients over SSE or streamable HTTP. MCP clients can build and run n8n workflows, and admins oversee connected MCP clients and can revoke their consent. A public REST API is available and can be disabled. Custom and community nodes extend the catalog, npm modules can be enabled in the Code node, and .n8np packages export workflows, folders or whole projects as portable files with a manifest, size limits and API key scopes. An OEM path embeds n8n in another product using OAuth 2.0 token exchange, iframe SSO and delegated API access. Sourcedocs.n8n.io MCP Server Trigger, connect to n8n MCP server, n8n packages, security and OEM deployment pagesread 2026-08-31 |
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Relevance AIAPIs, SDKs & MCP Extensibility A TypeScript SDK, @relevanceai/sdk, runs agents, tasks, messages and workforces with streaming, an API trigger covers other languages, and an MCP server at mcp.relevanceai.com gives MCP clients OAuth access to a project's agents, tools and knowledge. Sourcerelevanceai.com/docs/sdk/introduction.mdread 2026-09-27 |
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Testing, Debugging & Optimization Testing, debugging, scoring, retries, fallbacks, quality gates, and optimization loops for improving agent workflows before and after deployment. |
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n8nTesting, Debugging & Optimization Evaluation and Evaluation Trigger core nodes ship with the platform. Builders run quick evaluations during development against known test cases and use metric based evaluations to measure, score and improve production workflow performance over time, with guidance on why to test and how to fix common issues. Debugging uses pin and mock data, debug executions that copy earlier execution data into the current workflow, manual and partial runs, and dirty node tracking. Sourcedocs.n8n.io test and improve AI workflows section, Evaluation and Evaluation Trigger nodes, understand executions pagesread 2026-08-31 |
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Relevance AITesting, Debugging & Optimization Test sets hold tests that simulate users and are scored by reusable checks, so versions can be compared on the same tests; publishing can require chosen test sets to pass at a minimum rate and block on failure, and monitor dashboards score live tasks against the same criteria with sampling and trend charts. Agent evaluations sit on the Enterprise plan. Sourcerelevanceai.com/docs/build/agents/evals/introduction.mdread 2026-09-27 |
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| Specialist automation | ||
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Browser & Computer Use Browser, desktop, or remote/local computer control for workflows that cannot be handled through stable APIs alone. |
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n8nBrowser & Computer Use n8n ships an Airtop app node that controls a cloud based web browser for querying, scraping and interacting with web pages, with operations to manage browser sessions and windows and to click an element, fill a form, hover, scroll and type, authenticated with Airtop credentials. Airtop is a third party browser engine wired in through a node, not a browser n8n ships itself. None of n8n's core nodes is a browser, desktop or computer use node, and SSH and Execute Command run commands on remote hosts. Sourcedocs.n8n.io Airtop node pageread 2026-09-29 |
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Relevance AIBrowser & Computer Use Browser steps (click, type, scroll by natural language or selector) run through Airtop, a separately sold browser engine that needs the customer's own Airtop account and API key. Relevance AI does not describe a browser or computer use agent of its own. Sourcerelevanceai.com/docs/build/tools/tool-steps/airtop-browser-automation/page-interaction.mdread 2026-09-27 |
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Pricing snapshot
Sourced from the Index pricing dataset · open each vendor's profile for full detail.
| Pricing | n n8n |
R Relevance AI |
|---|---|---|
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Entry price Lowest public entry point |
Starter from €20 a month billed annually (€24 monthly), Pro €50 (€60 monthly), Business €667 (€800 monthly) and Enterprise custom. The self hosted Community Edition is free. | Pro at $19 a month billed annually or $29 monthly, Team at $234 a month billed annually or $349 monthly, and Enterprise at custom pricing. |
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Pricing confidence How public the numbers are |
Public, partial | Public, partial |
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Billing Primary billing axis |
Tiered subscriptions priced in euros, each with a monthly allowance of workflow executions. One full run of a workflow counts as one execution, however many steps it has. | A plan subscription with two meters. Actions count each tool run, and Vendor Credits pay model and tool costs at provider rates with no markup. |
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Variable cost Workload / overage exposure |
Medium variable cost | High variable cost |
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Free tier / trial Try before you buy |
Free tierTrial
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No free tier
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Buying motion Self-serve vs sales call |
Mixed | Self-serve |
Both are independent. Relevance AI is the trading name of OnSearch Pty Ltd, and n8n is made by Berlin based n8n GmbH. Relevance AI's Pro plan is $19 a month billed annually and Team $234, with usage metered in Actions and Vendor Credits and no free plan. n8n Cloud starts at €20 a month billed annually, and the self hosted Community Edition is free.
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