Integrations

Supercharge Cisco Meraki with Relevance AI

Cisco Meraki is a cloud-managed networking solution that simplifies the management of network devices and infrastructure. With Relevance AI, you can leverage advanced AI capabilities to automate and optimize your network operations, ensuring efficiency and reliability.

Give your AI Agents Cisco Meraki Superpowers

Cisco Meraki provides a comprehensive platform for managing network infrastructure with ease. Relevance AI enhances this by enabling intelligent AI Agents to automate tasks, optimize configurations, and streamline network management processes.

Network Intelligence Mastery

The AI agent gains deep insights into network patterns and performance metrics for predictive optimization

Security Threat Orchestration

Automated detection and response to security threats across distributed networks in real-time

Analytics-Driven Decision Making

Transformation of complex network data into actionable insights for strategic infrastructure planning

Tools

Equip AI Agents with the Cisco Meraki Tools they need

Relevance AI empowers you to integrate Cisco Meraki tools seamlessly into your automated workflows.

Cisco Meraki - Create Organization
Creates a new organization within the Cisco Meraki cloud platform, establishing the top-level container for managing networks, devices, and configurations.
Cisco Meraki - Get Network
Retrieves detailed information about a specific network within a Cisco Meraki organization, including its configuration and status details.
Cisco Meraki - Get Network
Retrieves detailed information about a specific network within a Cisco Meraki organization, including its configuration and status details.
Cisco Meraki - Update Network
Modifies existing network settings within a Cisco Meraki organization, allowing changes to network name, timezone, tags, enrollment strings, and device status page accessibility.
Name
Cisco Meraki API Call
Description
Make an authorized request to a Cisco Meraki API
Parameters
["OAuth authentication", "HTTP methods (GET, POST, PUT, DELETE, PATCH)", "Custom headers", "Request body configuration", "Response handling"]
Use Case
A network administrator uses this integration to automatically monitor and update Meraki network configurations across multiple locations, enabling them to quickly respond to security incidents and maintain consistent network policies without manual intervention.

Security & Reliability

The integration between Cisco Meraki and Relevance AI utilizes secure OAuth authentication, ensuring that only authorized workflows can access your Meraki network data. Relevance AI manages API operations (such as creating organizations, retrieving network details, and updating settings) seamlessly in the background, allowing you to focus on higher-level tasks without worrying about errors, formatting, or API limits.

With built-in validation and type conversion, your workflows will operate smoothly, even when dealing with varying data formats. This integration empowers you to automate network management and configuration, streamlining your organizational setup and control while maintaining secure API-based operations.

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.

Get Started

Best Practices for Non-Technical Users

To get the most out of the Cisco Meraki + Relevance AI integration without writing code:
  • Start with a clear organization structure: Ensure your Meraki organizations and networks are well-defined for easier management.
  • Utilize pre-built workflows: Relevance AI provides templates for common tasks like creating organizations and updating network settings—perfect for quick implementation.
  • Connect securely: Verify that you have the correct OAuth credentials and permissions set up for your Meraki account during integration.
  • Test API calls: Use test networks and organizations to validate your API calls before applying changes to production environments.
  • Monitor API usage: Keep an eye on rate limits and implement error handling to manage API response issues effectively.