Time & Attendance System

Part of the worlds-biggest-software-project initiative.

An AI-native, open-source time and attendance platform with self-hosted biometrics, automated compliance, and natural-language scheduling.

Time & Attendance System is a workforce time-capture, scheduling, and compliance platform built for organisations that need accurate clock-in data, FLSA- and EU Working Time Directive-compliant overtime calculation, and full data sovereignty over biometric records. It is designed for SMBs and mid-market employers who cannot justify the $25–$41 per-employee/month cost of UKG or Ceridian Dayforce, but require more compliance depth than free tools like Homebase or Jibble can offer.

Why Time & Attendance System?

Incumbents are expensive and slow to deploy. UKG Ready and UKG Pro charge $25–$41 per employee per month with 6–12 month implementation timelines, putting the market leader out of reach for the SMB and mid-market segments.
The only credible OSS option is dated. TimeTrex (AGPL-3.0) is the sole open-source workforce management platform with biometric features, but its UI is described as functional but dated and its AGPL copyleft creates friction for organisations integrating it into hosted products.
Free tiers lack compliance depth. Homebase and Jibble serve micro-businesses well but provide minimal FMLA tracking, no DCAA support, and limited overtime rule configuration — leaving the 5–500 employee segment underserved.
Biometric data sovereignty is unmet. Biometric data is sensitive under GDPR Article 9, Illinois BIPA, Texas CUBI, and Washington My Health MY Data Act. No SaaS vendor can fully satisfy regulated-industry requirements for on-premises biometric processing.
Scheduling UX is largely form-based. No incumbent currently accepts plain-language scheduling instructions, forcing managers to navigate calendar grids and drop-down menus for routine shift work.

Key Features

Time Capture & Verification

Clock-in via web browser, mobile app, and software-based kiosk on existing tablet hardware
GPS geofencing to restrict clock-in to authorised work locations
Facial recognition on commodity Android/iOS devices using open-source embedding models, with on-device processing only
Manager timesheet approval workflow with full audit trail (change history, timestamps, approver identity)
Employee self-service portal: view schedule, request time off, review and dispute own timesheets

Compliance & Pay Rules

FLSA-compliant overtime calculation with configurable daily, weekly, and California double-time rules
FMLA and state-level leave tracking with protected absence coding
EU Working Time Directive rules: 48-hour maximum, rest period enforcement
Real-time compliance alerting before violations occur (approaching overtime, missed rest periods, geofencing anomalies)
DCAA-compliant timekeeping mode for U.S. government contractors with contemporaneous recording and supervisor approval

Scheduling

Shift scheduling with availability management, conflict detection, and coverage rules
AI-based demand forecasting using historical attendance patterns
Natural language schedule requests for managers ("Cover Tuesday night shift with 3 certified staff, avoid overtime")
Shift swap workflows with optional manager approval

Payroll Integration

CSV export and direct integration with QuickBooks and Xero at minimum
Standard payroll connector formats compatible with ADP, Gusto, and Paychex workflows
iCalendar (RFC 5545) export for employee calendar apps

Data Sovereignty & Deployment

Self-hosted deployment option with biometric data processed entirely on-premises
Open-source biometric libraries with disclosed model identity for auditability
No vendor data access required for biometric or attendance records

AI-Native Advantage

AI-optimised shift scheduling can balance demand forecasting, employee preferences, labour-law constraints, and cost targets simultaneously — research suggests this can reduce scheduling time from hours to minutes and cut overtime costs by 15–25 percent. Anomaly detection flags buddy-punching patterns, geofencing violations, and approaching overtime thresholds in real time, turning reactive compliance into proactive risk management. Natural language schedule management eliminates the need for grid-based scheduling UIs and reduces the training burden on shift supervisors. Predictive absence forecasting anticipates high-absence periods from historical patterns so coverage can be adjusted before gaps appear.

Tech Stack & Deployment

The platform targets a self-hosted-first deployment model for biometric data sovereignty, with a hosted option for organisations preferring managed infrastructure. Facial recognition runs on commodity Android/iOS hardware using OpenCV-based open-source embedding models (e.g. FaceNet, DeepFace), eliminating the $500–$2,000 per-terminal cost of proprietary biometric clocks. Integrations follow open standards: iCalendar (RFC 5545) for schedule export, HR Open Standards for HRIS data exchange, and ISO/IEC 19794-4 for biometric data interchange. A REST API and standard CSV/XML payroll exports support QuickBooks, Xero, and connector-based integration with ADP, Gusto, Paychex, and Ceridian.

Market Context

The Time & Attendance Systems market is estimated at $3.6B in 2026 and projected to reach $6.95B by 2035 (Kings Research); broader segmentations including hardware project $7.9B by 2026 (Market Research Future). UKG holds approximately 34.8 percent market share (AppsRunTheWorld, 2025), with pricing of $25–$41 per employee per month leaving a clear gap for the SMB and mid-market. Primary buyers are VPs of HR and HR Directors at 200–5,000-employee retail and manufacturing companies, payroll managers focused on FLSA/FMLA audit defence, and operations managers needing mobile clock-in and real-time attendance visibility.

Project Status

This project is in the research and specification phase.
Contributions, feedback, and domain expertise are welcome.

Contributing

We welcome contributions from developers, domain experts, and potential users. See CONTRIBUTING.md for guidelines.

Important: All contributions must be your own original work or clearly attributed open-source material with a compatible licence. Copyright infringement and licence violations will not be tolerated and will result in immediate removal of the offending contribution. If you are unsure whether a piece of code, text, or other material is safe to contribute, open an issue and ask before submitting.

Licence

Licence to be determined. See discussion for context.