AIP-C01 · Question #1
AIP-C01 Question #1: Real Exam Question with Answer & Explanation
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Question
A financial services company is building a customer support application that retrieves relevant financial regulation documents from a database based on semantic similarity to user queries. The application must integrate with Amazon Bedrock to generate responses. The application must search documents in English, Spanish, and Portuguese. The application must filter documents by metadata such as publication date, regulatory agency, and document type. The database stores approximately 10 million document embeddings. To minimize operational overhead, the company wants a solution that minimizes management and maintenance effort while providing low-latency responses for real-time customer interactions. Which solution will meet these requirements?
Options
- AUse Amazon OpenSearch Serverless to provide vector search capabilities and metadata filtering.
- BDeploy an Amazon Aurora PostgreSQL database with the pgvector extension. Store embeddings
- CUse Amazon S3 Vectors to configure a vector index and non-filterable metadata fields. Integrate
- DSet up an Amazon Neptune Analytics database with a vector index. Use graph-based retrieval
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