Improve Contract Search Accuracy with Auto-Generated Filters in Amazon Bedrock

Enterprises managing large volumes of complex legal agreements face challenges in efficiently retrieving relevant contract information. Amazon Bedrock's AI-Driven Annotation (AIDA) system addresses this by transforming unstructured contracts into searchable, actionable data. AIDA employs a Retrieval-Augmented Generation (RAG) architecture that combines semantic search with metadata filtering to enhance accuracy.

The system begins with document ingestion, where contracts are uploaded into Amazon Bedrock Knowledge Bases with structured metadata such as parties, dates, jurisdiction, and other key attributes. This metadata enables powerful filtering capabilities downstream. During processing, contracts are segmented into semantically meaningful chunks, optimized for retrieval, and stored as vector embeddings in secure, encrypted vector databases like Amazon OpenSearch Service or Amazon S3 Vectors.

When a user submits a query, AIDA converts it into embeddings and applies both implicit (metadata-based) and explicit (application-level) filters before performing semantic search. This two-stage filtering narrows down the candidate pool to the most relevant documents, improving retrieval precision. The retrieved chunks are then used to augment the user's query, providing context for Amazon Bedrock's large language models (LLMs) to generate precise, grounded responses.

AIDA also incorporates safeguards such as Amazon Bedrock Guardrails to prevent prompt injections and data leaks, ensuring secure and compliant operation. The final response is delivered with source attribution, enabling traceability and reducing hallucinations common in LLM outputs.

Extensive testing demonstrates that combining filtering and metadata enrichment yields the most accurate results, especially for complex legal queries like identifying expired licensing agreements governed by specific laws. This approach enhances confidence in AI-generated contract insights, supporting legal review and decision-making.

Overall, AIDA's integration of filtering, metadata enrichment, and secure retrieval pipelines offers a practical, enterprise-ready solution for contract intelligence, reducing manual review efforts and unlocking the value of contractual data.