Home
World Journal of Advanced Research and Reviews
International Journal with High Impact Factor for fast publication of Research and Review articles

Main navigation

  • Home
    • Journal Information
    • Editorial Board Members
    • Reviewer Panel
    • Abstracting and Indexing
    • Journal Policies
    • Our CrossMark Policy
    • Publication Ethics
    • Issue in Progress
    • Current Issue
    • Past Issues
    • Instructions for Authors
    • Article processing fee
    • Track Manuscript Status
    • Get Publication Certificate
    • Join Editorial Board
    • Join Reviewer Panel
  • Contact us
  • Downloads

eISSN: 2581-9615 || CODEN: WJARAI || Impact Factor 8.2 ||  CrossRef DOI

Research and review articles are invited for publication in March 2026 (Volume 29, Issue 3) Submit manuscript

GirGut: An AI-powered, developer-First AB testing platform mimicking natural selection for web application

Breadcrumb

  • Home
  • GirGut: An AI-powered, developer-First AB testing platform mimicking natural selection for web application

Leela Gowtham Yanamaddi 1, * and Balaji Kummari 2

1 CEO and VP of Engineering, scale.jobs 537 Payne Rd, Woodstock, GA, USA 30188.
2 CTO, scale.jobs 1-84, Beside Venugopala Swamy Temple, Rayanapadu, Vijayawada, AP 521241, India.
 
Research Article
World Journal of Advanced Research and Reviews, 2024, 21(02), 2035-2044
Article DOI: 10.30574/wjarr.2024.21.2.0406
DOI url: https://doi.org/10.30574/wjarr.2024.21.2.0406
 
Received on 15 January 2024; revised on 23 February 2024; accepted on 28 February 2024
 
A high-quality product experience is becoming more important to consumers as a whole as a result of societal progress. The competition is constantly raising the bar for product specifics in their pursuit of a high profit conversion rate. Rapid, high-quality product iteration is essential for product providers looking to increase user viscosity and activity, which in turn increases the profit conversion rate. By inserting logs and analysing statistical data, A/B testing can determine which iterative strategy is more effective by conducting experiments on target users. This paper introduces GirGut, an innovative, open-source AB testing platform designed specifically for web developers. GirGut leverages artificial intelligence to generate and evolve test variants, mimicking the process of natural selection to optimize user engagement and conversion rates. By combining ease of use with powerful AI capabilities, GirGut aims to revolutionize the way developers approach experimentation and optimization in web applications.
 
AI-Powered; AB Testing; Web Applications; Product
 
https://wjarr.com/sites/default/files/fulltext_pdf/WJARR-2024-0406.pdf

Preview Article PDF

Leela Gowtham Yanamaddi and Balaji Kummari. GirGut: An AI-powered, developer-First AB testing platform mimicking natural selection for web application. World Journal of Advanced Research and Reviews, 2024, 21(2), 2035-2044. Article DOI: https://doi.org/10.30574/wjarr.2024.21.2.0406

Copyright © Author(s). All rights reserved. This article is published under the terms of the Creative Commons Attribution 4.0 International License (CC BY 4.0), which permits use, sharing, adaptation, distribution, and reproduction in any medium or format, as long as appropriate credit is given to the original author(s) and source, a link to the license is provided, and any changes made are indicated.


All statements, opinions, and data contained in this publication are solely those of the individual author(s) and contributor(s). The journal, editors, reviewers, and publisher disclaim any responsibility or liability for the content, including accuracy, completeness, or any consequences arising from its use.

Get Certificates

Get Publication Certificate

Download LoA

Check Corssref DOI details

Issue details

Issue Cover Page

Editorial Board

Table of content

Copyright © 2026 World Journal of Advanced Research and Reviews - All rights reserved

Developed & Designed by VS Infosolution