EconPapers    
Economics at your fingertips  
 

Transforming Enterprise Document Management: AWS AI and RPA Integration

Manoj Kumar Reddy Jaggavarapu ()

International Journal of Computing and Engineering, 2025, vol. 7, issue 15, 50 - 69

Abstract: Merging Amazon Web Services (AWS) AI tools with Robotic Process Automation (RPA) creates game-changing possibilities for companies drowning in paperwork. Every day, businesses wade through thousands of documents - a nightmare of inefficiency that drains resources and breeds mistakes. This fresh approach puts AWS Textract at the heart of the solution, giving machines the power to truly understand documents rather than just reading words. In comparison to the old-school scanning technology, Textract understands the context and association of information. Include Amazon Comprehend to the equation and, all of a sudden, these documents show patterns, sentiments, and vital information points without the need for human eyes to read each page. RPA bots tie everything together, acting as digital workers connecting these smart tools to existing business systems. Organizations embracing this approach see remarkable changes: paperwork that once took days now processes in minutes, accuracy jumps dramatically, systems run non-stop, costs plummet, and regulatory compliance becomes more consistent. This isn't just about doing paperwork faster - it completely reimagines how information moves through an organization, giving businesses entirely new ways to innovate and serve customers better in today's digital landscape.

Keywords: Intelligent Document Processing; AWS AI Services; Robotic Process Automation; Workflow Automation; Document Intelligence (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://carijournals.org/journals/index.php/IJCE/article/view/3011 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bhx:ojijce:v:7:y:2025:i:15:p:50-69:id:3011

Access Statistics for this article

More articles in International Journal of Computing and Engineering from CARI Journals Limited
Bibliographic data for series maintained by Chief Editor ().

 
Page updated 2025-07-25
Handle: RePEc:bhx:ojijce:v:7:y:2025:i:15:p:50-69:id:3011