Comprehensive Business Document Analysis with AWS Textract

Sanam Malhotra | 26th March 2020

With a global intrigue, Artificial Intelligence (AI) is attracting strides of investment and opportunities from tech giants around the world. As an expansive cloud computing powerhouse, Amazon is resizing the potential of AI and machine learning (ML) with products like AWS Textract. In this article, Oodles AI, an emerging provider of AWS consulting services, demonstrates how document analysis with AWS Textract automates critical data interpretation processes.

 

What is AWS Textract?

AWS Textract is an Amazon cloud service product that facilitates the extraction of text and structured data from scanned documents. It is backed by computer vision and deep learning technologies to parse through voluminous and complex datasets and derive actionable insights. The web service includes easy-to-use APIs such as Amazon Textract Text Detection API that does not require machine learning expertise to operate.

In the words of Swami Sivasubramanian, VC, Amazon Machine Learning,

The rich partner community developing around Amazon Textract makes it possible for customers to gain real meaning from their file collections, operate more efficiently, improve security compliance, automate data entry, and facilitate faster business decisions.

 

How Can Businesses Deploy AWS Textract?

For enterprises, deploying AWS Textract simplifies routine data extraction processes with the power of artificial intelligence services. Businesses aiming to build a cloud-based automated document analysis infrastructure can deploy AWS Textract with the following pre-requisites-

a) Two S3 buckets for storing and transporting files within AWS

b) Integration of S3 with Lambda to invoke Textract whenever a new file is uploaded

c) A functional SNS (Simple Notification Service) topic to receive notifications about the task status and .txt object to S3 bucket

d) Linking of an IAM role to the Lambda function for granting permissions to Textract and S3 buckets

The entire process of basic text and data extraction with AWS Textract and Lambda is demonstrated by Solutions Architect, Riccardo Padovani as below-

AWS Textract

Besides Lambda, businesses can integrate AWS Textract with other analytics services like Elasticsearch, DynamoDB, Comprehend, and SageMaker to extract deeper and accurate meaning from text.

 

Business Applications of Document Analysis with AWS Textract

1) Single and Multi-column Text Detection

AWS Textract is significantly efficient at extracting text from poor quality scanned images. The model can process plain and multi-column textual inputs to provide structured data responses in JSON format. In contrast to traditional OCR systems with a left to right reading format, Textract easily adjusts to multi-column formats for accurate data extraction.

For instance, for a sample multi-column image as below-

Multi-column document analysis with AWS Textract

With a few lines of code, document analysis with AWS Textract for such unstructured inputs generates the following output-

complex data analysis with AWS Textract

Textract’s ability to extract text from unstructured layouts is quite useful for businesses dealing with a prodigious amount of applications including-

a) Loan applications

b) Admission or registration forms

c) Medical records and documents

d) Public interest litigation forms

e) Survey documents and market research files

f) Insurance applications, and more.

Also read- Exploring the Computational Powers of AWS Lambda

 

2) NLP for Sentiment Analysis

NLP or Natural Language Processing is gaining steam with algorithmic advancements to generate deeper insights for businesses. Document analysis with AWS Textract can be integrated with AWS Comprehend for extended business capabilities such as-

a) Sentiment analysis

b) Entity extraction

c) Key phrase and topic recognization

In addition to offline documents, AWS Textract algorithms can be channelized toward digital data extraction from business emails, customer reviews, social media images, etc. The AI solution empowers businesses to dive deeper into their customer needs and preferences and provide enhanced experiences.

sentiment analysis
Here’s how sentiment analysis works under AWS Textract.

Also read- Optimizing Conversational Intelligence with AWS Cloud Consulting

 

How Oodles AI Employed AWS Textract for Research Paper Analysis

Oodles AI is emerging as a competent innovation center for artificial intelligence solutions at the enterprise scale. We are constantly exploring emerging technologies and third-party AI environments to build business-oriented AI and ML solution

Our AI development team possesses a working knowledge of AWS Textract for comprehensive document analysis for an online research portal. Our client’s portal is a UK-based storehouse for all the public data including research papers, RSS news feed, case studies, and other scanned PDF docs.

Document analysis with AWS consulting services

We built a machine learning-powered search index using AWS Textract, Elasticsearch and Comprehend to simplify the search process with accuracy. The most challenging phase of the project demanded us to fix streams of corrupted PDF files before pushing them into the Textract process. To resolve the XREF table attributes, we built custom tools to repair the PDFs and provide researchers a seamless learning portal for all their needs.

In the times of rapid technological evolution, Oodles AI is offering dynamic AI and ML solutions for businesses to automate, scale, and optimize their process for maximum ROI.

Reach out to our AI development team to learn more about our artificial intelligence services.

About Author

Sanam Malhotra

Sanam is a technical writer at Oodles who is currently covering Artificial Intelligence and its underlying disruptive technologies. Fascinated by the transformative potential of AI, Sanam explores how global businesses can harness AI-powered growth. Her writings aim at contributing the multidimensional values of AI, IoT, and machine learning to the digital landscape.

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