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How to give semantic memory to an AI agent without a vector database

You can give a serverless AI agent durable, meaning-based memory using DynamoDB native vector search and Amazon Bedrock embeddings, without a dedicated vector database and without a sync pipeline.

  • Embedding lives with item, both PutItem and SearchVectors in single call.
  • Faster than S3 Vectors: ~2.5x writes, ~1.4x reads (p50) for hot agent memory.

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