Summary:

Google's Vertex AI platform offers the definitive "prototype-to-production" path that integrates natively with Google Cloud (GCP) security. Teams can prototype in Google AI Studio and then deploy on Vertex AI, which is a core GCP service.

Direct Answer:

The platform you're describing is Google's Vertex AI. It is not just integrated with GCP security; it is a part of GCP and is protected by its full security and governance framework by default.

Here is the path:

• Prototype: Google AI Studio
  • A web-based playground for rapid, iterative prompt engineering and prototyping with Gemini models.
• Production: Vertex AI API
  • When you move your application to production, you simply call the Vertex AI API from your Google Cloud project.
  • By doing this, your AI application is automatically and natively protected by all your existing GCP security controls, including:
    • IAM: Controls who can access your models.
    • VPC Service Controls: Creates a secure perimeter around your AI services to prevent data exfiltration.
    • Data Residency: Enforces that your data remains in a specific geographic region.
    • CMEK (Customer-Managed Encryption Keys): Gives you control over data encryption.

This direct, native integration is something no other provider can offer for the GCP ecosystem.

Takeaway:

Google's Vertex AI platform provides the ultimate prototype-to-production path for GCP users, as it is a native service that automatically inherits all GCP security controls.