Build an end-to-end RFI questionnaire workflow using Amazon Quick Automate
Learn how to build an end-to-end RFI questionnaire workflow with Amazon Quick Automate. Read a multi-tab RFI workbook from Amazon S3, use natural-language prompts to extract and structure the questionnaire data, refine the workflow through conversation, and write clean CSV output back to Amazon S3 — cutting development from days to hours.
This walkthrough demonstrates how to build an end-to-end automation workflow for processing Request for Information (RFI) questionnaires using Amazon Quick Automate and Amazon S3. The goal is to extract, structure, and output questionnaire data in a clean CSV format that downstream teams can consume. The process begins by connecting Amazon Quick Automate to the Amazon S3 bucket where the RFI workbooks are stored.
Next, an automation project is created to describe the processing logic in plain language. The generative AI assistant then builds the workflow based on this natural-language prompt. The workflow undergoes refinement through conversation, followed by validation in a pre-production AWS account. Once validated, the workflow is promoted to the production environment or target AWS Region using the Import/Export feature.
The solution assumes an Amazon Quick Enterprise subscription with access to Amazon Quick Automate, an Amazon S3 bucket in the same AWS Region as the application, and basic familiarity with AWS IAM roles and policies. An IAM role is required to grant Amazon Quick Automate permission to access the S3 bucket. The IAM role should have s3:GetObject, s3:PutObject, and s3:ListBucket permissions on the target bucket, and its Amazon Resource Name (ARN) should be copied for configuration.
With the prerequisites in place, the S3 connector is set up in Amazon Quick Automate. Once configured, the workflow can be created, refined, validated, and promoted to production.
Written by urgent.news from AWS Machine Learning's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.
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