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dc.contributor.author | Muhammad Fawaz Khalid, 01-131212-021 | |
dc.contributor.author | Muhammad Gulsher Khan, 01-131212-022 | |
dc.date.accessioned | 2025-06-18T04:24:52Z | |
dc.date.available | 2025-06-18T04:24:52Z | |
dc.date.issued | 2025 | |
dc.identifier.uri | http://hdl.handle.net/123456789/19631 | |
dc.description | Supervised by Dr. Adeel Muzaffar Sayed | en_US |
dc.description.abstract | Integrating new employees into an organization, commonly known as onboarding, is a very critical process in any company but is often implemented ineffectively. Traditional methods rely on methods that are manual, time-consuming, costly and may also fail to provide any customization to the training on onboarding process. This project “KuickBoard” addresses these challenges trough a platform made to streamline and automate the key functions of employee assessments and onboarding by generating courses and assessments using Artificial Intelligence. The purpose behind KuickBoard is to lessen the burden on the administration, make training customizable and easy, and encourage employee engagement and skill development from the first day that they enter the company. KuickBoard was implemented as a web application. The frontend user interface was made using Angular because of its component-based structure. The backend of the website was built using .NET Core framework. The system architecture follows the Model-View-ViewModel (MVVM) pattern, promoting separation of concerns. Data storage is handled by a MySQL relational database, and user authentication is managed via JSON Web Tokens (JWT). The AI used for course and assessment generation were mainly ChatGPT 3.5 turbo and Gemini 2.0 Flash. The KuickBoard prototype has a multitude of core functionalities. These include user management for both individual learners and company employees, capabilities for companies to manage their profiles, teams, roles, and employee invitations, and most importantly, AI-powered features for generating candidate assessments and employee training courses based on prompts. The platform also includes mechanisms for assigning courses to employees and tracking their progress. In conclusion, this project is a platform that demonstrates the potential benefits of an AI-powered approach to employee onboarding and assessment. It successfully meets the primary goals of automating training and providing a centralized system. The platform is a step towards more efficient, scalable, and potentially customizable corporate onboarding strategies. While acknowledging the necessity for future work, particularly in areas such as AI bias prevention, advanced analytics, broader third-party system integrations, and comprehensive user testing, KuickBoard effectively lays the groundwork for a next-generation onboarding solution. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Software Engineering, Bahria University Engineering School Islamabad | en_US |
dc.relation.ispartofseries | BSE;P-3003 | |
dc.subject | Software Engineering | en_US |
dc.subject | Critical Components and Best Practices | en_US |
dc.subject | Building and Cultural Integration | en_US |
dc.title | KuickBoard - AI Driven Employee On boarding and Assessment Platform | en_US |
dc.type | Project Reports | en_US |