Integrations

Supercharge Gryd with Relevance AI

Gryd is an integration platform that offers real-time access to vehicle data through a robust API suite. By combining Gryd with Relevance AI, you can build powerful applications that utilize vehicle information for enhanced analytics and operational efficiency.

Give your AI Agents Gryd Superpowers

Gryd provides instant access to comprehensive vehicle information, while Relevance AI empowers you to leverage that data with intelligent AI Agents for smarter decision-making and automation.

Seamless Vehicle Data Orchestration

Enables AI agents to instantly access and process comprehensive vehicle information across multiple regulatory databases.

Real-time Compliance Intelligence

Empowers agents to make instant decisions based on live ULEZ and MOT compliance data from authoritative sources.

Predictive Fleet Intelligence

Enables agents to anticipate vehicle maintenance needs and compliance issues before they become problems.

Tools

Equip AI Agents with the Gryd Tools they need

Relevance AI integrates seamlessly with Gryd to enhance your workflows with real-time vehicle data insights.

Gryd - Get Vehicle DVLA Data
Retrieves official DVLA (Driver and Vehicle Licensing Agency) registration and licensing data for a specified vehicle using its VRM (Vehicle Registration Mark)
Gryd - Get Vehicle MOT Data
Fetches Ministry of Transport (MOT) test history and certification information for a specific vehicle, including test results and advisory notices
Gryd - Get Vehicle MOT Data
Fetches Ministry of Transport (MOT) test history and certification information for a specific vehicle, including test results and advisory notices
Gryd - Get Vehicle ULEZ Data
Checks Ultra Low Emission Zone (ULEZ) compliance status and related information for a vehicle, helping determine if it meets environmental standards
Gryd - Get Vehicle Data
Retrieves comprehensive vehicle information including technical specifications, registration details, and other general vehicle data
Name
Gryd API Call
Description
Make an authorized request to a Gryd API
Parameters
["OAuth authentication", "Multiple HTTP methods (GET, POST, PUT, DELETE, PATCH)", "Custom headers support", "Request body configuration", "Response handling with status codes"]
Use Case
A data analytics team uses Gryd API Call to automatically fetch and process customer behavior data across multiple applications, enabling them to create real-time dashboards and trigger automated responses based on specific user actions.
Quick Start

Connect Gryd to Relevance AI in minutes

Security & Reliability

The Gryd integration platform provides secure OAuth-based authentication, ensuring that only authorized applications can access real-time vehicle data. With Relevance AI, API operations such as fetching DVLA, MOT, and ULEZ information are handled seamlessly in the background, allowing developers to focus on building robust vehicle-data-driven applications without worrying about errors or data formatting.

Built-in validation ensures that vehicle registration marks (VRM) are correctly formatted, while comprehensive error handling and caching mechanisms enhance performance and reliability, even under high load conditions.

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 Gryd + Relevance AI integration without writing code:
  • Start with a clear vehicle data structure: Use consistent vehicle registration mark (VRM) formats and ensure all required fields are populated.
  • Utilize built-in functions: Relevance AI provides pre-built functions for fetching vehicle data, MOT history, and ULEZ compliance—perfect for quick implementation.
  • Authenticate securely: Ensure you use the correct OAuth credentials and permissions during setup to avoid authentication issues.
  • Test API calls with sample data: Validate your API requests with known VRMs to ensure accuracy before deploying in a live environment.
  • Monitor API usage: Implement request throttling and caching to manage rate limits and optimize performance.