Automated attendance saves hours every day, but only if consent, retention and accuracy are designed in from the first sprint.
Start with the lawful basis
Biometric data is sensitive almost everywhere. Decide who consents, how a person opts out, and what the manual fallback is before choosing a camera. India's DPDP Act and GDPR-style regimes both expect purpose limitation and a clear retention period.
Store templates, not photographs
Keep only the mathematical template needed to match a face, encrypt it, and delete it when a person leaves. Raw frames should be processed and discarded unless an incident review requires them.
Measure false-accept and false-reject rates on your own lighting and camera angles, not on the vendor demo set.
Design for exceptions
Masks, new haircuts and poor light will happen. A fast manual override with an audit trail keeps the line moving and gives you the data to tune thresholds.
Working through this in your organisation?
Talk to the team behind our Attendance Intelligence practice about what a practical first step looks like for you.