Answer: Knowledge base

Amazon Bedrock Knowledge Bases is the correct approach for this use case. Here's why: - **Knowledge Bases** allow you to connect foundation models to your company's data sources, including S3 buckets - They can ingest documents from S3 and create vector embeddings for retrieval-augmented generation (RAG) - This enables the chatbot to combine general AI knowledge with specific information from the university's internal research papers - The chatbot can then provide responses that are grounded in both the foundation model's general knowledge and the specific research content Other options: - **Agents**: Used for multi-step tasks and tool use, not specifically for connecting to knowledge sources - **Guardrails**: Focus on safety and content filtering - **Model evaluation**: Used for testing and comparing model performance Knowledge Bases is specifically designed for the scenario described - augmenting foundation models with custom data sources like S3-stored documents.

Author: Ritesh Yadav