CLOCKIN¶
AI · Face Recognition · Mobile · Backend
An intelligent attendance management system that automates employee check-ins using AI-driven facial recognition eliminating manual registers and proxy attendance.
The Problem¶
For most organisations, tracking attendance is still a manual, error-prone process. Sign-in sheets, card swipes, and PIN-based systems were built for a different era. They create problems that quietly compound over time.
The most common issue is buddy punching, where one employee clocks in on behalf of another. It is more widespread than most HR teams realise, and it directly inflates payroll costs. Beyond that, manual registers are slow to process, easy to falsify, and produce no structured data that managers can actually act on. Generating a weekly attendance report often means someone spending hours reconciling spreadsheets by hand.
For businesses managing shift workers, field teams, or distributed staff, the gaps are even wider:
- There is no way to confirm that the person who clocked in is actually on-site
- Late arrivals and early exits go unnoticed without a supervisor present
- Payroll disputes are hard to resolve because records are incomplete or inconsistent
- HR spends significant time on administrative follow-up that should not exist
The deeper issue is that attendance data, when captured properly, is genuinely valuable. It feeds into payroll accuracy, shift planning, compliance reporting, and workforce productivity analysis. But legacy systems capture almost none of that value. They just record a timestamp and stop there.
Organisations needed something that could verify identity reliably, capture location context, surface exceptions automatically, and feed clean data into the tools they already use, without adding friction to the employee experience.
The Solution¶
CLOCKIN replaces manual attendance processes with an AI-powered system that uses facial recognition to verify and log employee presence. Key capabilities include:
- Automated face-based check-in and check-out with liveness detection
- Real-time attendance dashboard for managers and HR
- Automated daily/weekly reports with exception flagging
- Mobile app for on-site and remote team management
- Location-aware check-in with GPS verification
- Integration-ready with payroll and HR systems
Technology Used¶
| Layer | Stack |
|---|---|
| AI / Recognition | Python · Face Recognition · OpenCV |
| Backend | Python · FastAPI |
| Mobile | Jetpack Compose · Android |
| Database | PostgreSQL |
| Infrastructure | AWS · Docker |