KAIROS FOR HUMAN CAPITAL MANAGEMENT

Identify. Verify. Keep Track.

 

 

Most folks know Kairos as an industry leading provider of face recognition software. And we are. But what’s mostly unknown, is that the very first product we developed and sold, exclusively, was for biometric time keeping. That’s right. We were a time clock company! It was actually our entire business.

 

Since we’ve been away, some workforce challenges have been solved— while others still need solutions. We’re stoked to see that so many businesses have transitioned away from timesheets to automated timekeeping Yet we’re concerned to see that counterproductive work behaviors like time theft continue to plague un protected business. So we’re back in the game— bringing leading edge workforce solutions, and a name businesses already trust.

 

Integrate, Verify, and Track.

We don't require expensive hardware. Devs can integrate face Kairos biometric identity verification right into existing timekeeping platforms. In fact, most smart devices can serve as Kairos kiosks!

How it works

Employees enroll into Kairos by taking a front facing selfie. Then, we link enrolled photos to relevant information like employee IDs or schedules. When a person’s face is scanned for ‘clock in’, Kairos compares their face to all employee enrolled images to find a match.

If a match is found, the system approves the person as an employee and timestamps the entry-- making Kairos an identity verification and time tracking tool.

BUILD YOUR OWN MOBILE TIME CLOCK

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Since employees can only 'clock in' with their faces from your location, they cannot punch in for each other. Kairos face recognition eliminates 'buddy punching' and remote check ins.

Wait, hard working people cheat?

They do. In fact, nearly half [1] of US workers admit to having committed time theft. And while we don’t often like to think about dishonest characteristics of the human experience— in business— ignoring them can negatively impact ROI, and enable the behaviors to spiral out of control over time.

According to a study by the American Payroll Association Counterproductive Work Behavior (CWB) is quite costly— with time theft affecting more than 75% [2] of US businesses, causing them to lose an average of 2.2% of their gross payroll annually [3]. It’s actually estimated that embezzlement of time costs U.S. employers more than $400 billion [4] per year in lost productivity. Four hundred billion?

A Flexible Solution

We think government regulated employee safeguards around things like paid maternity leave & meal and rest breaks, are fantastic. Everyone in the workforce deserves to be treated fairly. Including employers. Kairos levels workforce fairness by nearly eliminating occurrences of the following Counterproductive Work Behaviors:

  • Buddy Punching – Exactly what it sounds like. Employee: “Hey I’ll be about 10 minutes late-- can you clock me in?” Friend: “Sure. See you when you get here.”
  • Time Clock Manipulation – Employee accesses the time clock setup in order to fraudulently adjust his time, or even a friend’s time.
  • Unsecured Computer – An unsecure computer can be used to manipulate time by employees who clock in and out by logging into a computer.

As a workplace grows, Kairos can grow with it. It’s really as easy as installing a few more kiosks or an API integration into a mobile app. And since Kairos works with smart devices, you can carry it around during field work, too. We offer mobility and flexibility for a myriad of workforce management needs— offering organizations the tools to confidently rely on workers, and accurately track time.

[1] https://www.softwareadvice.com/hr/industryview/time-theft-report-2015/
[2] https://www.replicon.com/wp-content/uploads/2016/06/Whitepaper_ROI_Considerations_TA-1.pdf
[3] https://nucleusresearch.com/valuematrix/
[4] https://www.epaysystems.com/time-theft-facts-and-stats/

Build Your Own iOS Face Recognition Timeclock

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7 Lessons from Building a Face Recognition Time Clock

Photograph of a young woman using the time clock app, overlayed by drawings that explain the Face Recognition API's enroll method

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