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Developers building RAG applications on Bedrock now have a concrete pattern for improving retrieval accuracy in high-stakes domains like legal; enterprises evaluating Bedrock for knowledge-heavy workloads gain evidence that the platform's Knowledge Bases can handle complex filtering and context requirements.
AWS describes how AIDA, a contract search system built on Amazon Bedrock, improves search accuracy through auto-generated filters, implicit/explicit filtering, and metadata-enriched chunking in Knowledge Bases. The approach addresses legal use cases where context and access boundaries matter for retrieval-augmented generation.
Read the full article at AWS AI/ML
CoFabrix summarises and comments on this story. The original reporting belongs to AWS AI/ML.
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