Building a privacy preserving chatbot with Amazon Bedrock

This article discusses an approach to building a privacy-preserving chatbot using Amazon Bedrock and Skyflow Data Privacy Vault. It highlights the importance of safeguarding sensitive data like personally identifiable information (PII) throughout the AI model lifecycle.

Specifically, the article covers:

• The need to protect sensitive data from exposure, especially in multi-tenant chatbot environments
• Skyflow's data privacy vault for sensitive data detection, de-identification, and fine-grained access control
• Preserving privacy during data ingestion and vectorization using Skyflow as a privacy gateway
• Preserving privacy during inference by integrating Skyflow for de-identifying PII in prompts
• An architecture for privacy-safe multi-tenant chatbot with Amazon Bedrock, EKS, DynamoDB, and Skyflow
• Conclusion on the benefits of using Skyflow for deploying privacy-preserving AI on AWS