Universal Containers wants its AI agent to answer customer questions with precise and up-to-date
information. How does an Agentforce Data Library simplify and enable this?
A. It automates the ingestion, taxonomical classification and storage of knowledge in Data Cloud for precision keyword search retrieval to ground prompts and agents with relevant information.
B. It automates the ingestion, Indexing of data, and creates a default retriever to be used in prompts and agents for grounding with relevant information.
C. It automates the ingestion and optical character recognition (OCR) processing of any PDF, and indexes them to enable regular SQL query retrieval to ground prompts and agents with relevant information.
B. It automates the ingestion, Indexing of data, and creates a default retriever to be used in prompts and agents for grounding with relevant information.
Explanation:
The AgentForce Data Library simplifies AI-powered responses by:
Automating Data Preparation
1. Ingests documents (e.g., PDFs, Knowledge articles) into Data Cloud.
2. Indexes content for semantic search (not just keywords).
3. Creates a default retriever to fetch the most relevant data for grounding prompts.
Enabling Precise, Up-to-Date Answers
1. Agents/prompts use the retriever to pull fresh, verified information (e.g., "What’s the current return policy?").
2. Avoids hallucinations by grounding responses in trusted sources.
Why Not the Other Options?
A. "Taxonomical classification":
While useful, the Data Library focuses on indexing/retrieval, not manual taxonomy building.
C. "OCR + SQL queries":
The Data Library uses vector search, not SQL, for AI grounding.
Reference:
Salesforce Help - AgentForce Data Library