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Team members

Stephen Alvin (EPD), Philip Andrew Wee De Wang (EPD), Son Soo Han (ESD), Low En (ISTD), Wong Ye Qi Daryll (ISTD)


Norman Lee Tiong Seng, Ying Xu, Mohan Rajesh Elara, Nuno Ribeiro

Writing Instructors:

Wong Yoke Chee Susan

Teaching Assistant:

Cheryl Low Rui Min


Talent attrition is too expensive for organizations.


➤ 20% of employees quit their job in the first 45 days

➤ Organizations spend an average of 6-9 months worth of the position's salary replacing the lost talent


This is a serious concern for many companies who are struggling with attracting and retaining top talents


Through our customer interviews, we discovered that organizing mentorship programmes is one key area that can help to keep employees engaged and retain talents. However, there are many challenges with organizing a mentorship programme.

Challenges with Organizing Mentorship Programmes

After interviewing more than 60 professionals from Human Resources, Organization Development and Talent Management, here's what we found:


➤ More than 50% don't enjoy their mentorship experiences

  • ➤ Mentors and mentees don't know how to conduct mentorship sessions
  • ➤ Manual matching of mentors and mentees takes a lot of time and effort
  • ➤ Laborious to organize surveys and feedback
  • ➤ Inconvenient and hard to analyze survey data points

Aurient - A Tool for the Future of Work

A tool for the Future of Work: Aurient


1. Personality, Skills, and Competency Profiling


To allow for more effective matching, we collected essential information from the mentors and mentees.

From our customer interviews, effective mentorship matching needs to consider the following qualities to create compatible matches:

⓵ Personal Mentorship Goals

⓶ Personality Traits - MBTI

⓷ Technical Skills and Competencies


2. Intelligent AI Matching Algorithm


With the profile information collected from the mentors and mentees, we were able to use this information to create a recommendation engine to easily suggest matches, saving 2-3 hours per match.

There are two ways to match:

⓵ Manual matching for each mentor and mentee

Talent managers may consider the suggestions and reasons for compatibility made by the recommendation engine, and make manual matching of mentor and mentee pairs.


⓶ Automatic matching for all mentees in the programme

This can help save a lot of time spent in matching in a large programme with many participants.

3. Guided and Reviewed Mentorship Sessions


To produce better outcomes for the mentorship programme, the mentoring sessions have to be conducted effectively and with valuable inputs and feedbacks.

⓵ Guiding the mentorship session

We do this through guiding the discussion around the pre-planned agenda points and mentorship goals of the mentees.

⓶ Post-meeting Feedback

Mentors and mentees can give feedback and suggestions after each mentorship session so both mentors and mentees are able to improve themselves after every session.

4. Progress Tracking with Data-Driven Insights


Organizations and Talent Managers need concrete data points to help them make decisions. We provide an analytics dashboard for talent managers to conveniently access these data points to understand their employees better and to help improve mentorship programmes.

Talent managers are able to get these insights:

➤ Overall satisfaction levels of the programme


➤ Track the progress of the meetings


➤ Understand the general goal profiles of mentors and mentees


➤ Important Mentorship Objectives

-   Sharing of Valuable Experiences

-   Handing Down of Managerial Practices

-   Exployee Engagement

Feedback from Users


Some feedbacks from users after trying out Aurient

"I can see myself saving a lot of time organizing a large scale mentorship programme for my company"

  1. "I waste the most time when I have to gather feedbacks and data points after each mentorship programme. Having integrated feedback mechanism and the accessible data points would really help cut down a lot of my time and give me concrete improvement areas."

"One of my largest problems is matching the correct mentors to mentees as all of them have different goals and personalities, and it gets really complex real quick if we have a lot of participants in the mentorship programme. I like that Aurient can help to suggest the matches automatically"

"I really love the feedback and insights from the feedbacks. It gives me a good idea of how to improve current processes and even my organization development porcesses."




From the aurient team, we would like to sincerely thank everyone who has supported and contributed to us in any way.

This journey has been extremely fulfilling for all of us. Doing an entrepreneurship project is probably one of the best choices we have made in our university lives. It has allowed us to go through numerous stages of product discovery and customer interviews, countless product iterations and product development. This would not have been possible without the support of our industry mentor, Andeed, SUTD Entrepreneurship Centre, Capstone Instructors, Prof. Mohan Rajesh Elara, Prof. Norman Lee, Prof. Ying Xu, Dr. Susan Wong, and everyone who has helped us through our journey.

A big thank you from Team Aurient!  👋👋👋

grp photo



student Stephen Alvin Engineering Product Development
student Philip Andrew Wee De Wang Engineering Product Development
student Son Soo Han Engineering Systems and Design
student Low En Information Systems Technology and Design
student Wong Ye Qi Daryll Information Systems Technology and Design
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