Author
Listed:
- Omkar Shewale
(Department of Information Technology Trinity College of Engineering and Research Savitribai Phule Pune University, Pune, Maharashtra, India)
- Prathamesh Shinde
(Department of Information Technology Trinity College of Engineering and Research Savitribai Phule Pune University, Pune, Maharashtra, India)
- Jayesh Upare
(Department of Information Technology Trinity College of Engineering and Research Savitribai Phule Pune University, Pune, Maharashtra, India)
- Prof. Pravin Patil
(Department of Information Technology Trinity College of Engineering and Research Savitribai Phule Pune University, Pune, Maharashtra, India)
Abstract
In the modern digital era, users frequently rely on different applications for tasks such as content writing, plagiarism detection, text summarization, interview preparation, and image editing. Managing multiple platforms for these activities often interrupts workflow, increases effort, and affects overall productivity. To simplify this process, this paper introduces Quick.ai, an AI-powered Software-as-a-Service (SaaS) platform that combines several intelligent tools into a single web application. The platform is developed using the PERN stack, which includes PostgreSQL, Express.js, React.js, and Node.js, allowing the system to remain scalable, responsive, and efficient. Quick.ai provides features such as Post Creator, Prompt Generator, Text Summarizer, Plagiarism Checker, Interview Question Generator, Repurpose Engine, Background Removal, and Object Removal. Testing and evaluation of the platform showed improved workflow management and stable performance across all modules. The system achieved a content quality score of 4.3 out of 5, text summarization accuracy of 87%, and image processing accuracy ranging from 70% to 80%.
Suggested Citation
Omkar Shewale & Prathamesh Shinde & Jayesh Upare & Prof. Pravin Patil, 2026.
"Unified AI-Based SaaS Platform Delivering Comprehensive Integrated Services,"
International Journal of Latest Technology in Engineering, Management & Applied Science, RSIS International, vol. 15(5), pages 3077-3089, May.
Handle:
RePEc:bjf:ijltem:v:15:y:2026:i:5:a:2679
DOI: 10.51583/IJLTEMAS.2026.150500251
Download full text from publisher
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bjf:ijltem:v:15:y:2026:i:5:a:2679. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no bibliographic references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Dr. Pawan Verma (email available below). General contact details of provider: https://www.ijltemas.in/ .
Please note that corrections may take a couple of weeks to filter through
the various RePEc services.