Summary

Client Shreyans Gangwal Country India
Project scope and technology HRMS, Machine Learning, Face Recognition Industry Human Resource
Team Composition 1 Project Manager, 2 AI developers, 1 Machine Learning Developer, 1 QA, 1 Business Analyst Work duration 6 Months

PRAAVI HRMS is a pioneering machine learning-based attendance mobile app designed and developed for businesses. The application uses face recognition technology to capture images and mark employee attendance. It also tags employees' locations to ensure they are where they should be.

It offers quick staff onboarding, access to attendance summaries and reports, a complete staff directory, allows supervisors to manage employees’ shifts on multi-location, and assign roles to the staff.

The HRMS app also has a distinctive feature known as ‘Attendance Alerts’, that detects fraudulent approaches by employees to mark attendances, wrong locations, wrong timings, etc., and alerts the supervisors or team leaders.

With PRAAVI HRMS, businesses can embrace a seamless, secure, and transparent approach to workforce management.

Challenge

The client approached us with an idea to create an intelligent attendance tracking and staff management application tailored for small and medium-sized enterprises (SMEs).

The idea behind the development of PRAAVI HRMS arose from the frequent issues of irregular attendance among staff members.

Recognizing the negative impact of fraudulent attendance practices on business productivity, our client was looking for a solution to tackle this challenge.

PRAAVI HRMS is an ML-based attendance tracking and management system that makes attendance precise.

The app has cutting-edge features making it the best all-in-one solution for attendance management.

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Process

Post brainstorming sessions with the client, our team began the development of the HRMS system. Our experienced developers designed an intuitive user interface, prioritizing user-friendliness to ensure seamless navigation and operation of the software.

Simultaneously, our AI and machine learning developers were crafting advanced algorithms and integrating face recognition into the HRMS mobile application to empower it to manage attendance tracking and streamline employee management processes with unparalleled accuracy.

Apart from this, we also added additional features, such as location tagging, staff directory, attendance reports, shift management, etc. as requested by the client. Our commitment to meeting and exceeding client expectations resulted in seamless integration of these features, ensuring a comprehensive solution tailored to the client's needs.

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Key Features of PRAAVI HRMS

  • Facial Recognition-Based Attendance Marking
  • Location Tagging
  • Quick Onboarding
  • Attendance Summaries and Reports
  • Assign Roles
  • Detailed Attendance Records
  • Shift and Multi-Location Management
  • Attendance Alerts
  • Staff Directory
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The Outcome of Our Dedication

After months of unmatched dedication and hard work, we are proud to develop PRAAVI HRMS, a groundbreaking ML-based HRMS application, developed to disrupt the market.

The software leverages face recognition technology to capture pictures of staff and mark attendance. It also seamlessly tags employee locations, empowering supervisors with real-time insights into staff whereabouts.

Not only this, but the HRMS application also helps with assigning staff roles, accessing attendance reports, providing a complete staff directory, and managing manpower shifts in multiple locations.

In essence, PRAAVI HRMS represents the pinnacle of HR management applications, offering unparalleled efficiency, accuracy, and versatility to businesses of all sizes.

2 Weeks

Ideation and Designing

22 weeks

Development

1 week

Testing

1 week

Deployment
Design
Development
Project Duration

I extend my deepest appreciation to Quytech for their outstanding work in developing the HRMS app. Their team's professionalism, expertise, and unwavering dedication to excellence have surpassed my expectations. The seamless functionality and innovative features of the system have left a lasting impression on me. Thank you, Quytech, for your exceptional service!

Shreyans

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