Hi Community members @trust_level_0 , 
In today’s digital landscape, AI is becoming a game-changer to boost efficiency and unlock new possibilities across various aspects of life.
We at Katalon recently wrapped up our first-ever internal Hackathon: Thrive with AI 
. We wanted to connect creative minds and empower every Katalian, regardless of their technical expertise, to learn, build, and play with this new technology.
During the event, participants attended Tech seminars to gain essential AI/ML knowledge and insights into Katalon’s Generative AI (GenAI) services. Then, from March 20-21, 2024, we encouraged them to team up and incorporate GenAI within Katalon’s products – think new features to supercharge user testing or ways to make automation testing a breeze for manual testers.
We are excited to share some of the standout projects from the Hackathon below. Vote for your favorite – the one that resonates most with you as a Katalon user! 
You can vote up to three (3) projects.
From now until 2024-04-07T16:59:00Z, simply:
- Take a look through the projects below by clicking on the link to each team’s submission.
- Cast your vote(s) in the poll at the end of this post, and
- Reply to this thread and share with us what your favorite idea(s) was/were and why you chose them, alongside a lucky number.
- Five (5) members who completed step 3 will get a chance to win a $25 eGift Card each!
After 2024-04-07T16:59:00Z, we will host a lucky draw to determine the winners.
Already seen all the projects? Then cast your vote(s) here.
Hackathon’s projects
| Project 1 |
Project 2 |
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| Team’s name: R&A |
Team’s name: SR |
Project description: Katzard - Automated root cause analysis, where magic happens. (1) Group failed results by similar exception; (2) AI analyzes the data; (3) Return root causes & solutions recommendations.
Check out their project here |
Project description: Semantic Object locator that make use of Large Language Model and Multimodal Large Language Model for noticeable improvement in healing failure test.
Check out their project here |
| Project 3 |
Project 4 |
|
|
| Team’s name: COYTE |
Team’s name: ai-kìa |
Project description: Uses contextual text and image information including business requirements, generation requirements, and visual inputs about the SUT in recording sessions for the test case generation.
Check out their project here |
Project description: Konsultant with Error Log explanation that can explain Error stacktrace of KS users; and User interface enhancement, adding the explanation dialog to KS UI.
Check out their project here |
| Project 5 |
Project 6 |
|
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| Team’s name: G5&Friends |
Team’s name: GenFAI |
Project description: KataAccessible - Accessibility testing & beyond. A solution to reach the Accessibility Testing Market (projected to reach USD 759M by 2032), ensure legal compliance, and user experience, and make Katalon a pioneer in AI accessibility.
Check out their project here |
Project description: AI-powered knowledge graph that can visualize the connections between requirements, enabling users to easily navigate and explore their interdependencies. Thus, quickly identify impacted areas arising from requirement changes.
Check out their project here |
| Project 7 |
Project 8 |
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| Team’s name: ABCD |
Team’s name: PolyJuice |
Project description: AI-powered Full Flow Automation Testing without coding that address critical challenges in web application development, leading to increased efficiency, improved test coverage, faster releases, and empowered QA teams.
Check out their project here |
Project description: A library or Katalon keyword for Katalon Studio to help reduce the cost of test case maintenance by reducing the need to update existing test scripts when changes to web applications are made in the software development lifecycle.
Check out their project here |
Vote for your favourite project(s) here
Which project(s) from Katalon Hackathon did you like?
- [R&A Team] Katzard - Automated root cause analysis
- [SR Team] Semantic Object Locator
- [COYTE Team] Test Case Generation using contextual text and image information
- [ai-kìa Team] Konsultant with Error Log explanation
- [ G5&Friends Team] KataAccessible - Accessibility testing & beyond
- [GENFAI Team] AI-powered knowledge graph that can visualize the connections between requirements
- [ABCD Team] AI-powered Full Flow Automation Testing without coding
- [PolyJuice Team] A library of Katalon keywords for Katalon Studio to help reduce the cost of test case maintenance
3 Likes
End to End Flow Automation Testing without coding seems like a low code no code / codeless stack and a nice Feature. Luck Number 7
6 Likes
The visual view of the project 7 is interesting, ideal for those who prefer a high-level perspective like me. Full flow automation testing without coding project seems to reduce setup efforts for Katalon on TestOps.
6 Likes
- Project 6: Gen FAI (Lucky number - 1)
Favorite Idea: The AI-powered knowledge graph that visualizes connections between requirements.
Reason for Choosing: This idea stands out because it addresses a critical aspect of software development – managing requirements and understanding their interdependencies. The ability to quickly identify impacted areas due to requirement changes can significantly streamline the development process and minimize risks associated with misunderstandings or oversights in requirements management.
- Project 7: ABCD
Favorite Idea: AI-powered Full Flow Automation Testing without coding.
Reason for Choosing: This idea is intriguing because it represents a significant advancement in software testing methodology. Full flow automation testing without coding not only accelerates the testing process but also empowers QA teams by allowing them to focus on higher-level testing tasks such as strategy development, analysis, and optimization. It aligns with the ongoing trend of automating repetitive tasks to enhance productivity and efficiency in software development.
- Project 1: R&A
Favorite Idea: Katzard - Automated root cause analysis.
Reason for Choosing: Root cause analysis is a fundamental aspect of troubleshooting and debugging in software development. Automating this process using AI can save significant time and effort for developers, enabling them to quickly identify and address issues. By providing actionable insights and recommendations, Katzard has the potential to streamline the debugging process and improve the overall reliability and stability of software systems.
These ideas were selected based on their potential to address critical challenges in software development, their alignment with emerging trends in AI and automation, and their potential to deliver tangible benefits to development teams and end-users alike.
5 Likes
I like the AI-powered Full Flow Automation Testing without coding because I feel like it will help manual QA analyst
2 Likes
I have Chosen Katazard, its a great feature which will help to reduce time in identifying logs and revisng and fixing cases , where we can enable in bulk .
This feature will help to analyse the issues and multiple ways to solve it .
this will help to cummunity and great idea
This is agreat feature hope this gets enabled in coming days.
My Lucky Num is 39
1 Like
Love the idea of having AI applied to Accessibility testing!
1 Like
I have voted ABCD Team AI-Powered Full Flow Automation Testing because Automating the scenarios without coding is what required in today’s generation. and if correct prompt engineers is assigned to the task he can use the AI and automate the application
My lucky Number is- 99
5 Likes
Hi @here,
Thank you for your enthusiasm thus far! 
We would like to remind you that for you to win the prizes, you will need to:
- Cast your vote(s) in the poll here, and
- Reply to this thread and share with us what your favorite idea(s) was/were, why you chose them, alongside a lucky number.
Please double check your current reply and add in your lucky number (if needed).
(If you have already done the two steps above then please disregard this reply).
Thanks,
Albert
Lucky Number 143
- [ABCD Team] AI-powered Full Flow Automation Testing without coding
This idea is intriguing even though it exists now in many formats it still needs extreme human intervention I hope AI-powered full-flow automation will replace those challenges in the future. it may accelerate the testing process but, also allows QA teams to focus on higher-level testing tasks and negative test flows. It is essential for the ongoing trend of automating repetitive tasks.
- [ai-kìa Team ] Konsultant with Error Log explanation
I’m choosing this because most of the time new testers face challenges in understanding the test logs and error logs. This consumes a huge time in understanding the error logs and this reduces their productivity too. I hope this project will help to reduce the time taken to maintain the test projects into half
5 Likes
Hi Bharathi,
Thanks for casting your votes for the Hackathon projects.
Remember to also include a lucky number in your reply so that you can participate in our lucky draw as well! 
1 Like
One idea for improving the semantic object locator project is to integrate real-time image processing capabilities with the Large Language Model (LLM) and Multimodal Large Language Model (MMLM). This integration would allow the system to analyze images or video streams in conjunction with textual descriptions to accurately locate objects within a given environment. By combining visual information with natural language understanding, the system can achieve a more comprehensive understanding of the context, leading to better object localization results.
Another idea is to implement a reinforcement learning component within the system. This would enable the semantic object locator to learn and adapt over time based on feedback from users or from its own performance evaluations. Reinforcement learning can help the system improve its accuracy and efficiency by iteratively refining its strategies for object localization.
I chose these ideas R&A Team because they leverage the strengths of both language processing and visual recognition technologies, allowing for a more holistic approach to object localization. By incorporating real-time processing and reinforcement learning, the system can continuously improve its performance and adapt to changing environments or requirements.
Lucky number: 7
2 Likes
Project 7 stands out for its innovative approach to software testing. This AI-powered tool automates entire test flows without requiring any coding. This translates to a much faster testing process, freeing up QA teams to tackle more strategic tasks like test planning, analysis, and improvement. This aligns perfectly with the growing trend of automation to boost efficiency and productivity in software development.
Project 1 tackles a central challenge in software development: pinpointing the root cause of problems. “Katzard” leverages AI to automate this process, saving developers significant time and effort. By automatically identifying issues and offering actionable recommendations, Katzard has the potential to significantly streamline debugging, leading to more reliable and stable software.
Project 4 Given the focus on user experience and potential for efficient development, Konsultant seems like the most fitting choice. It empowers users, reduces support load, and might be easier to implement due to its modular design.
My lucky number is 21
5 Likes
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Konsultant with Error Log explanation: Feel there is indeed much optimization possibilities here. Now when a test fails we need to a) scroll to try and find the error & line number of the script that goes wrong. b) interpret the error based on the piece of code and possibly a screenshot (and even trying to reproduce it via debug-run to know what the heck goes on) c) come up with a solution. Would be very handy if somehow we could get all 3 solutions with a single click
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A library or Katalon keyword for Katalon Studio to help reduce the cost of test case maintenance: Like the team mentions, in agile development, the SUT (subject-under-test) tends to change a lot. Of course, goal as a tester is to make tests as robust as possible. But still, I estimate at least 75% of the test case failures in our TST environment our due to changing requirements, new features or even test data changes. So a lot of time is invested in keeping these tests up to date. I personally do not use the self-healing as it just doesn’t suit my needs (I use customized keywords and often inscript test objects). I often use the general ‘search and replace’ to fix broken locators. Any effort that could reduce that time is greatly appreciated.
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Katzard - Automated root cause analysis: Kind of the same reasons as both projects above. The group failed results by similar exception is something I often use in TestOps already. I do miss there currently the feature to be able to sort on time of occurrence. E.g., if a flaky test fails once a year due to a similar exception we can live with it. If it happens once a month, it needs a fix. Now there just sorted on similarity (I think).
Just hope these features will become available for current paying customers, not behind (another) license wall 
Thanks!
Lucky number: 123
1 Like
Hi folks @trust_level_0,
There are less than 3 days left until our voting poll is closed. Don’t miss out this chance to vote for your favorite Hackathon project, and get to win a $25 eGift card by doing so!
We look forward to seeing your votes!
Katalon Community team
Project : ABCD
End to End automation testing without using any code or scripts look advanced feature and it helps QA like us to do automation much quicker and increase our productivity. It is one of the great feature of Katalon.
Project : COYTE
Using AI for test case generator is one of the best way to generate missed use cases and it also reduces the complexity of the test cases it also helps to increase productivity of QA’s with this feature and it also helps in cost reduction.
Lucky Number : 4
2 Likes
Hi,
I have voted for project number 6, because I consider that any effort and innovation in the area of requirements using the new factor of Artificial Intelligence (AI) has a lot of potential and great impact on the projects, mainly where agile methodologies and Incremental Interactive development processes are used.
My lucky number is: 7
