Google Vertex AI is a powerful platform that simplifies the use of AI and machine learning through a user-friendly API. With Relevance AI, you can leverage these capabilities to create dynamic workflows that harness the full potential of AI-driven insights.
Google Vertex AI provides robust machine learning tools for tasks like sentiment analysis and media processing. Relevance AI amplifies these capabilities by enabling intelligent AI Agents that can automate and optimize your data-driven processes.
Cognitive Mastery
Empowers the agent with Google's advanced ML models for superior understanding and decision-making capabilities.
Adaptive Intelligence
Leverages AutoML to continuously evolve and improve performance through automated learning and optimization.
Multi-Modal Proficiency
Processes and analyzes diverse data types including text, images, and video through unified API endpoints.
Relevance AI seamlessly integrates with Google Vertex AI to enhance your workflows with advanced AI capabilities.
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 Google Vertex AI account
- A Relevance AI account with access to the project and datasets you'd like to use
- Authorization (you'll connect securely using API keys—no sensitive info stored manually)
Security & Reliability
The integration leverages Google's secure OAuth 2.0 authentication flow, ensuring only authorized workflows can access Vertex AI capabilities. Google Vertex AI handles complex machine learning operations in the background—managing model serving, API quotas, and input validation automatically.
Built-in error handling and response formatting ensure your AI workflows run reliably, with automatic retries and data type conversion for supported model endpoints.
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 Google Vertex AI + Relevance AI integration without writing code:
- Start with a clear project setup: Ensure your Google Cloud project is properly configured with the Vertex AI API enabled and necessary permissions granted.
- Utilize pre-built endpoints: Take advantage of Vertex AI's pre-built endpoints for common tasks like text sentiment analysis and image classification to streamline your workflow.
- Manage authentication carefully: Double-check your OAuth 2.0 credentials and ensure the correct scopes are set to avoid authentication issues.
- Test with sample data: Before deploying on live data, test your API calls with sample inputs to validate functionality and avoid errors.
- Monitor API usage: Keep an eye on your API quotas and usage patterns to prevent hitting rate limits and ensure smooth operation.
