Ngrok is a powerful tool for secure API gateway management and tunneling, allowing you to create and monitor HTTPS edges effortlessly. With Relevance AI, you can elevate this functionality by incorporating AI-driven automation into your workflows.
Ngrok provides secure tunneling and API gateway management, while Relevance AI empowers you to automate and optimize these processes with intelligent AI Agents that can adapt and respond to your needs.
Secure Gateway Mastery
Enables AI agents to securely access and interact with protected internal systems through encrypted tunnels
Real-Time Traffic Orchestration
Empowers agents to monitor, analyze, and respond to live request patterns and data flows instantly
Automated Security Compliance
Ensures all agent interactions meet industry standards through built-in encryption and access controls
Relevance AI seamlessly integrates with Ngrok to enhance your API management workflows.
What you’ll need
You don't need to be a developer to set up this integration. Follow this simple guide to get started:
- A Relevance AI account
- An Ngrok account with an active tunnel configured
- Authorization (you'll connect securely using OAuth—no sensitive info stored manually)
Security & Reliability
The Ngrok and Relevance AI integration utilizes secure OAuth authentication, ensuring that only authorized workflows can manage your API gateways and tunnels. This integration automates API operations (like creating, retrieving, updating, and deleting HTTPS edges) in the background—so you don’t have to worry about errors, formatting, or limits.
With built-in validation and streamlined edge management, you can easily configure and monitor your API gateways, ensuring that your applications run smoothly and securely, even in complex environments.
No training on your data
Your data remains private and is never utilized for model training purposes.
Security first
We never store anything we don’t need to. The inputs or outputs of your tools are never stored.
To get the most out of the Ngrok + Relevance AI integration without writing code:
- Start with clear edge descriptions: Use descriptive names for your edges to easily identify their purpose.
- Utilize metadata: Implement metadata tags for better organization and management of your edges.
- Secure your setup: Regularly rotate OAuth credentials and monitor access patterns to maintain security.
- Test configurations before deployment: Validate edge settings in a staging environment to avoid issues in production.
- Monitor performance: Keep an eye on response times and implement error handling to ensure smooth operations.
