[{"data":1,"prerenderedAt":36},["ShallowReactive",2],{"repo-amazon-serverless-knowyourcustomer-data":3},{"id":4,"title":5,"contributors":6,"date":8,"description":9,"diagram":10,"extension":11,"framework":12,"gitHub":14,"introBox":17,"language":21,"meta":23,"resources":24,"services":25,"simplicity":31,"stem":32,"type":33,"usecase":34,"__hash__":35},"repos\u002Frepos\u002Famazon-serverless-knowyourcustomer-data.json","Serverless architecture to identify KnowYourCustomer (KYC) data",[7],"content\u002Fcontributors\u002Fpaul-kannan.json","2023-07-21","Find PII data from wide variety of documents using AWS services.","\u002Fassets\u002Fimages\u002Frepos\u002Famazon-serverless-knowyourcustomer-data.jpg","json",[13],"Terraform",{"template":15},{"repoURL":16},"https:\u002F\u002Fgithub.com\u002Faws-samples\u002Famazon-serverless-knowyourcustomer-data",{"headline":5,"text":18},[19,20],"Customers are looking for ways to detect PII data from a wide variety of documents that the teams are handling and want to leverage services from Amazon in identification of PII, while allowing AWS to take care of the undifferentiated heavy lifting of the infrastructure.","In this code, I'm using serverless architecture to identify Know Your Customer (KYC) data from PDF documents uploaded into an Amazon S3 bucket. The PDF is passed as input to AWS Textract and the data is extracted from PDF. The extracted data is sent to a third party api to validate and based on the http response from external API, pass the concerned validation status to users through SQS and SNS, thereby helping customers to use the code as a template\u002Fpattern to build functionalities on top of the code.",[22],"Python",{},null,[26,27,28,29,30],"lambda-event-functions","s3","sfn","sns","sqs","200","repos\u002Famazon-serverless-knowyourcustomer-data","Application","Backend","YA8xydGX_LXeDxTk5v2kcSdcGO2dPRcsnGRF0yO6niw",1792578864590]