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|[Contract Compliance Analysis](samples/contract-compliance-analysis/)| This project automates the analysis of contracts by splitting them into clauses, determining clause types, evaluating compliance against a customer's legal guidelines, and assessing overall contract risk based on the number of compliant clauses. This is achieved through a workflow that leverages Large Language Models via Amazon Bedrock. | Backend + Frontend | Python for Backend, TypeScript (React) for Frontend |
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|[RFP Answers with GenAI](samples/rfp-answer-generation/)| This project provides guidance on how you can use Knowledge Bases for Amazon Bedrock with custom transformations to create draft answers for Request for Proposal (RFP) documents, streamlining the answer of new potential contracts. This is achieved through a workflow that leverages Large Language Models via Amazon Bedrock. | Backend + Frontend | Python for Backend, TypeScript (React) for Frontend |
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|[Code Expert](samples/code-expert/)| This project addresses the scalability limitations of manual code reviews by leveraging artificial intelligence to perform expert code reviews automatically. It leverages the [Bedrock Batch Step Functions CDK construct](https://github.com/awslabs/generative-ai-cdk-constructs/blob/main/src/patterns/gen-ai/aws-bedrock-batch-stepfn/README.md). | Backend | Python for Backend and Demo, TypeScript for CDK |
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|[Bedrock Agent UI Wrapper](samples/bedrock-agent-ui-wrapper/)| This sample provides a CDK construct that creates an API layer and frontend application for Amazon Bedrock Agents. It includes authentication with Amazon Cognito, agent trace streaming, and can be deployed locally or on ECS Fargate. | API layer + Frontend | Python|
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