QuinPlus (SAAS) helps the companies in informed decision making about hiring the right candidates
Quin AI
Artificial Intelligence and Machine learning provide an excellent virtual onboarding experience to the employees. Quin AI is perfect solution to the Inaccuracies in the employment information that may cause issues with the employee's job duties & their responsibilities it may also create confusion regarding their start date or compensation. Additionally, errors in forms may lead to non-compliance with legal and regulatory requirements, which could result in fines or penalties for the company.
Up until a couple of years ago artificial intelligence-based virtual onboarding was but a mere dream, But today it is reality and we at Quinfy are located at its epicentre and are providing a revolutionising and unique solution for virtual onboarding.
Aspects of Onboarding
The five most important aspects of onboarding are compliance, clarification, culture, connection, and check back. QUIN AI covers all this while including Artificial Intelligence to interact with the employee.Quinfy is a company that provides virtual onboarding solutions to employers, that aim to increase the employee experience and to provide a cost-effective way to onboard new hires.
User Onboarding experience
Documentations take a long time and chances of errors while filling various formsare high. QuinAI reduces the time taken by 90% thereby improving the employee onboarding experience while ensuring a near 100 % accuracy. Quinfy’s AI based onboarding solutions help you optimize and automate the entire employee onboarding journey while reducing the turnaround time.
Machine Learning and AI
Scan/upload pictures of your documents and you sit back and relax let Artificial Intelligence and machine learning fill those lengthy details for you. Just go through the documents once use a physical or digital signature and share it with HR.
Quinfy AI Solution automates the processing of employee forms and documents, ensuring compliance with labor laws and reducing the risk of errors.