n8n is a workflow automation platform that helps you connect different systems and automate tasks. While n8n delivers robust automation capabilities, Portkey adds essential enterprise controls for production deployments:

  • Unified AI Gateway - Single interface for 1600+ LLMs with API key management. (not just OpenAI & Anthropic)
  • Centralized AI observability: Real-time usage tracking for 40+ key metrics and logs for every request
  • Governance - Real-time spend tracking, set budget limits and RBAC in your n8n setup
  • Security Guardrails - PII detection, content filtering, and compliance controls

This guide will walk you through integrating Portkey with n8n and setting up essential enterprise features including usage tracking, access controls, and budget management.

If you are an enterprise looking to use n8n in your organisation, check out this section.

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1. Setting up Portkey

Portkey allows you to use 1600+ LLMs with your n8n setup, with minimal configuration required. Let’s set up the core components in Portkey that you’ll need for integration.

1

Create Virtual Key

Virtual Keys are Portkey’s secure way to manage your LLM provider API keys. Think of them like disposable credit cards for your LLM API keys, providing essential controls like:

  • Budget limits for API usage
  • Rate limiting capabilities
  • Secure API key storage

To create a virtual key: Go to Virtual Keys in the Portkey App. Save and copy the virtual key ID

Save your virtual key ID - you’ll need it for the next step.

2

Create Default Config

Configs in Portkey are JSON objects that define how your requests are routed. They help with implementing features like advanced routing, fallbacks, and retries.

We need to create a default config to route our requests to the virtual key created in Step 1.

To create your config:

  1. Go to Configs in Portkey dashboard
  2. Create new config with: 
    {
    "virtual_key": "YOUR_VIRTUAL_KEY_FROM_STEP1",
   	"override_params": {
      "model": "gpt-4o" // Your preferred model name
    }
}
  3. Save and note the Config name for the next step

This basic config connects to your virtual key. You can add more advanced portkey features later.

3

Configure Portkey API Key

Now create Portkey API key access point and attach the config you created in Step 2:

  1. Go to API Keys in Portkey and Create new API key
  2. Select your config from Step 2
  3. Generate and save your API key

Save your API key securely - you’ll need it for n8n integration.

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2. Integrate Portkey with n8n

Now that you have your Portkey components set up, let’s connect them to n8n. Since Portkey provides OpenAI API compatibility, integration is straightforward and requires just a few configuration steps in your n8n workflow.

You need your Portkey API Key from Step 1 before going further.

  1. In your n8n workflow, add the OpenAI node where you want to use an LLM
  2. Configure the OpenAI credentials with the following settings:
    • API Key: Your Portkey API key from the setup
    • Base URL: https://api.portkey.ai/v1

When saving your Portkey credentials in n8n, you may encounter an “Internal Server Error” or connection warning. This happens because n8n attempts to fetch available models from the API, but Portkey doesn’t expose a models endpoint in the same way OpenAI does. Despite this warning, your credentials are saved properly and will work in your workflows.

  1. In your workflow, configure the OpenAI node to use your preferred model
    • The model parameter in your config will override the default model in your n8n workflow

It is recommended that you define a comprehensive config in Portkey with your preferred LLM settings. This allows you to maintain all LLM settings in one place.

Make sure your virtual key has sufficient budget and rate limits for your expected usage. Also use the complete model name given by the provider.

You can monitor your requests and usage in the Portkey Dashboard.

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3. Set Up Enterprise Governance for n8n

Why Enterprise Governance? If you are using n8n inside your organization, you need to consider several governance aspects:

  • Cost Management: Controlling and tracking AI spending across teams
  • Access Control: Managing which teams can use specific models
  • Usage Analytics: Understanding how AI is being used across the organization
  • Security & Compliance: Maintaining enterprise security standards
  • Reliability: Ensuring consistent service across all users

Portkey adds a comprehensive governance layer to address these enterprise needs. Let’s implement these controls step by step.

Enterprise Implementation Guide

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Enterprise Features Now Available

n8n now has:

  • Departmental budget controls
  • Model access governance
  • Usage tracking & attribution
  • Security guardrails
  • Reliability features

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Portkey Features

Now that you have enterprise-grade n8n setup, let’s explore the comprehensive features Portkey provides to ensure secure, efficient, and cost-effective AI operations.

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1. Comprehensive Metrics

Using Portkey you can track 40+ key metrics including cost, token usage, response time, and performance across all your LLM providers in real time. You can also filter these metrics based on custom metadata that you can set in your configs. Learn more about metadata here.

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2. Advanced Logs

Portkey’s logging dashboard provides detailed logs for every request made to your LLMs. These logs include:

  • Complete request and response tracking
  • Metadata tags for filtering
  • Cost attribution and much more…

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3. Unified Access to 1600+ LLMs

You can easily switch between 1600+ LLMs. Call various LLMs such as Anthropic, Gemini, Mistral, Azure OpenAI, Google Vertex AI, AWS Bedrock, and many more by simply changing the virtual_key in your default config object.

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4. Advanced Metadata Tracking

Using Portkey, you can add custom metadata to your LLM requests for detailed tracking and analytics. Use metadata tags to filter logs, track usage, and attribute costs across departments and teams.

Custom Metadata

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5. Enterprise Access Management

Budget Controls

Set and manage spending limits across teams and departments. Control costs with granular budget limits and usage tracking.

Single Sign-On (SSO)

Enterprise-grade SSO integration with support for SAML 2.0, Okta, Azure AD, and custom providers for secure authentication.

Organization Management

Hierarchical organization structure with workspaces, teams, and role-based access control for enterprise-scale deployments.

Access Rules & Audit Logs

Comprehensive access control rules and detailed audit logging for security compliance and usage tracking.

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6. Reliability Features

Fallbacks

Automatically switch to backup targets if the primary target fails.

Conditional Routing

Route requests to different targets based on specified conditions.

Load Balancing

Distribute requests across multiple targets based on defined weights.

Caching

Enable caching of responses to improve performance and reduce costs.

Smart Retries

Automatic retry handling with exponential backoff for failed requests

Budget Limits

Set and manage budget limits across teams and departments. Control costs with granular budget limits and usage tracking.

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7. Advanced Guardrails

Protect your Project’s data and enhance reliability with real-time checks on LLM inputs and outputs. Leverage guardrails to:

  • Prevent sensitive data leaks
  • Enforce compliance with organizational policies
  • PII detection and masking
  • Content filtering
  • Custom security rules
  • Data compliance checks

Guardrails

Implement real-time protection for your LLM interactions with automatic detection and filtering of sensitive content, PII, and custom security rules. Enable comprehensive data protection while maintaining compliance with organizational policies.

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FAQs

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Next Steps

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For enterprise support and custom features, contact our enterprise team.