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This pioneering Chilean startup specializes in automating and centralizing expense reporting for companies of all types and currently operates in five Latin American countries. Their innovative approach has revolutionized how businesses manage their financial reporting and monitoring, setting new standards for efficiency in the region.
The client needed a tool that would allow users to accelerate the expense submission process. Specifically, the tool needed to analyze images or PDFs uploaded to the system, extracting key data from these documents. This process had to account for specific business rules and restrictions on expense claims, such as prohibiting claims for example alcoholic beverages during business meals.
After an in-depth analysis of image processing requirements, we developed a solution leveraging two AWS services: Amazon Textract and Amazon Bedrock. Amazon Textract is used to extract data fromfiles submitted by users, while Amazon Bedrock interprets this information according to the necessary business rules contained in a knowledge base. Finally, using Bedrock, we model the information to generate a payload that is sent back to the user’s application, automatically filling out the expense form.
Utilizing Amazon Bedrock's foundational models offers substantial benefits in the validation of business rules and the interpretation of information. These models excel in understanding complex text inputs and applying nuanced business logic, making them ideal for automating regulatory compliance and decision-making processes. This capability ensures that the system not only performs tasks automatically but does so with a highdegree of accuracy and in accordance with company policies.
The deployment of this AI-driven solution has significantly accelerated the expense reporting process for the client, reducing the time users spend interacting with the system. By automating the data entry process, our solution allows users to focus on merely verifying that the automatically populated information is correct, enhancing overall efficiency and user satisfaction with the expense reporting process.
The structured data is sent via API to the client's application, integrating extracted invoice data seamlessly into their workflow.
Metadata from invoice images and processing steps are stored in Amazon DynamoDB, enabling tracking of the extraction process and maintaining an operations log for audit and analytics.
The system uses AWS Lambda, which automatically scales in response to demand, and integrates with Amazon Textract for handling variable invoice image volumes. It is built on AWS services like S3, Lambda, Textract, SQS, and DynamoDB, which are designed for high availability across multiple zones.
Strict IAM policies ensure secure AWS service access, with DynamoDB tables secured by fine-grained controls. System health and performance are monitored via Amazon CloudWatch, with alerts for quick issue resolution.