The main benefit of using Amazon Textract needs improvement, specifically when we extract the tabular data, it is very complicated to get its coordinate functions. We get the coordinates for child and its parent and its child, which is very difficult to extract for the tabular structure or CSV format. Sometimes the tabular data does not process properly for complex tabular structures or complex tables. It would be helpful if we could improvise the model or the OCR solution to extract the complex tabular data and get its coordinates or bounding boxes for the tables, especially for complex tables. Apart from this tabular data, there is also no solution for checkbox detection. It would be helpful if we got a solution to detect the checkbox and get the bounding boxes for the checkbox and its value.
Software Engineer at Metatechno Lanka Company (Pvt.) Ltd.
Real User
Top 20
2025-04-09T09:24:39Z
Apr 9, 2025
The product has not given correct results for me. It was not accurate, especially with handwritten items and documents with pencil marks, which Amazon Textract ( /products/amazon-textract-reviews ) failed to identify correctly.
Find out what your peers are saying about Amazon Web Services (AWS), UiPath, Instabase and others in Intelligent Document Processing (IDP). Updated: September 2025.
Intelligent Document Processing utilizes AI technologies to streamline document-based workflows, reduce manual input, and increase efficiency in data extraction and processing.IDP integrates advanced technologies like machine learning, natural language processing, and computer vision to analyze unstructured data. It automates tasks like data extraction, classification, and validation, helping organizations minimize errors and process documents faster, thereby improving collaboration and...
The main benefit of using Amazon Textract needs improvement, specifically when we extract the tabular data, it is very complicated to get its coordinate functions. We get the coordinates for child and its parent and its child, which is very difficult to extract for the tabular structure or CSV format. Sometimes the tabular data does not process properly for complex tabular structures or complex tables. It would be helpful if we could improvise the model or the OCR solution to extract the complex tabular data and get its coordinates or bounding boxes for the tables, especially for complex tables. Apart from this tabular data, there is also no solution for checkbox detection. It would be helpful if we got a solution to detect the checkbox and get the bounding boxes for the checkbox and its value.
The product has not given correct results for me. It was not accurate, especially with handwritten items and documents with pencil marks, which Amazon Textract ( /products/amazon-textract-reviews ) failed to identify correctly.