Problem Statement
Our client was grappling with the laborious task of manually inspecting and extracting specific information from various types of documents, such as mortgages, legal papers, and court documents. This process was not only time-consuming but also prone to human errors. The client recognized the need for an automated solution to streamline their operations and enhance their overall efficiency.
Solution Overview
Our team implemented an end-to-end solution that encompassed both automated data extraction and human review. Here’s a breakdown of the solution.
Document Analysis and Information Extraction:
- Leveraged Google Vertex AI Vision to extract text from the documents, ensuring accurate retrieval of information.
- Trained a custom Machine Learning model using Google AutoML NLP to classify and identify the document type automatically.
- Implemented a rules engine that utilized the ML model’s output to extract the necessary information from each document.
Human Review Interface:
- Developed a browser-based application that provided a user-friendly interface for human review of the extraction process.
- This interface allowed human reviewers to validate and verify the accuracy of the extracted information, ensuring data quality.
Tech Stack leveraged
To address the client’s challenges and provide a robust solution, we harnessed the capabilities of Google Cloud Platform and leveraged the following technologies:
Google Vertex AI Vision:
- Utilized Vision AI to extract text from the diverse range of documents, predominantly in PDF format.
- Leveraged the power of Optical Character Recognition (OCR) to accurately capture textual information from scanned documents.
Google AutoML NLP:
- Trained a custom Machine Learning model using AutoML NLP to identify the document type automatically.
- Built a rules engine that allowed the system to extract the required information based on the document type identified by the ML model.
Benefits Delivered
Document Analysis and Information Extraction:
- Leveraged Google Vertex AI Vision to extract text from the documents, ensuring accurate retrieval of information.
- Trained a custom Machine Learning model using Google AutoML NLP to classify and identify the document type automatically.
- Implemented a rules engine that utilized the ML model’s output to extract the necessary information from each document.
Human Review Interface:
- Developed a browser-based application that provided a user-friendly interface for human review of the extraction process.
- This interface allowed human reviewers to validate and verify the accuracy of the extracted information, ensuring data quality.
By harnessing the capabilities of Google Vertex AI Vision and AutoML NLP, we developed a robust solution that revolutionized the document inspection and information extraction process. The outcome was an increase in efficiency, enhanced accuracy, and an overall improvement in the customer experience. We are committed to leveraging our technical intelligence to drive innovation and transform industries with AI-powered solutions.
