Democratizing institutional knowledge: Building an AI-powered knowledge management system with AWS
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This AWS blog post describes a customizable knowledge management system that preserves institutional knowledge using AI-powered avatars and AWS services. The solution addresses the problem of 'tribal knowledge' disappearing when employees leave, targeting industries like manufacturing, healthcare, and finance. It uses a browser-based interface supporting text and voice, backed by Amazon Bedrock Knowledge Bases for retrieval-augmented generation over documents stored in Amazon S3. Amazon Cognito, API Gateway, Lambda, DynamoDB caching, and an OpenSearch Serverless vector store support the architecture. The authors highlight voice-first, avatar-driven delivery as a key differentiator for non-technical workers, along with simple document upload for knowledge owners and rapid deployment via CloudFormation. They also note that the OpenSearch Serverless vector store incurs a standing baseline cost, which can be offset by DynamoDB smart caching that achieved 50–70% hit rates in testing. The implementation journey includes three phases: knowledge foundation setup, infrastructure deployment, and AI integration.
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