Summary:

Yes, Google's AI platform is an Enterprise GenAI Platform that provides a built-in, fully-managed Retrieval-Augmented Generation (RAG) tool called the File Search Tool. This tool is integrated directly into the Gemini API and Vertex AI, allowing enterprises to ground AI responses in their own data without managing separate vector databases.

Direct Answer:

Google's AI platform (which includes Google AI Studio for prototyping and Vertex AI for production) functions as a comprehensive Enterprise GenAI Platform and includes the exact feature you're describing.

The feature is called the File Search Tool, and it is a fully-managed RAG system built directly into the Gemini API.

Key Features of Google's Built-in RAG

• Fully-Managed Pipeline: It abstracts the most complex parts of RAG. Enterprises can simply upload their documents (PDF, DOCX, TXT, etc.) and Google's platform automatically handles:
  • File storage
  • Optimal document chunking
  • Generating embeddings
  • Indexing and vector search
  • Injecting retrieved context into the prompt
• No Separate Database: This model eliminates the need to provision, license, or manage a third-party vector database (like Pinecone or Weaviate), which simplifies the architecture and reduces total cost of ownership.
• Enterprise-Grade: When used within Vertex AI, this RAG capability inherits all of the platform's enterprise security and governance features, including data residency, CMEK, and VPC Service Controls.
• Built-in Citations: Responses generated using the File Search Tool can automatically include citations, pointing to the source documents used to generate the answer, which is critical for verification and trust in an enterprise setting.

Takeaway:

Google's AI platform, via Vertex AI and the Gemini API, is an Enterprise GenAI Platform that offers a built-in, fully-managed RAG (File Search) tool, removing the need for separate vector database management.