Mentr: A Modular, On Demand Mentorship Platform for Personalized Learning and Guidance
Muskaan Juneja , Founder - Mentr & WiseversityAbstract
Most mentorship and coaching programs today operate on a broken model - they bundle everything together and assume everyone needs the same help. Whether you're studying for competitive exams or navigating career changes, you're forced to pay for comprehensive packages even when you only need guidance in specific areas.
We experienced this problem firsthand. While preparing for civil services, one of us needed help only with modern history and parts of geography, yet had to enroll in expensive full-scale programs covering subjects she'd already mastered. Our other co-founder struggled to find relevant mentors through existing professional networks when facing crucial career decisions.
These frustrating experiences aren't unique. A survey of our 200,000-member community revealed that over 85% prefer personalized mentorship over generic coaching programs, highlighting a massive gap in the market.
Mentr addresses this problem directly. It's an on-demand mentorship platform where users can book live video calls with experts, join immediate sessions with available mentors, or access targeted video content - all focused on their specific needs. Rather than paying for unnecessary content, users get precise help when they need it.
Our platform uses AI-powered matching to connect mentees with relevant mentors based on their queries, not just keyword searches. We've built a modular system that scales individual components independently while maintaining quality through strict mentor vetting and continuous feedback analysis.
With plans to onboard 100+ mentors in year one, Mentr represents a fundamental shift toward accessible, personalized guidance that eliminates the inefficiencies of traditional bundled coaching models.
Keywords
On-demand learning, AI-powered mentor matching, Modular education platforms, Competitive exam guidance, Digital mentorship solutions, Affordable expert access, Career and life-stage coaching, Edtech innovation, Real-time mentor connectivity
References
Vishwakarma, S., Jain, S., Dashore, V., Soni, T., Kushwah, S., & Sharma, S. (2023). Mentor Connect: Facilitating meaningful professional and academic guidance through a digital platform. ResearchGate. https://www.researchgate.net/profile/Ijeasm-Journal/publication/388476322_Mentor_Connect_Facilitating_Meaningful_Professional_and_Academic_Guidance_Through_a_Digital_Platform/links/6799fcd6645e f274a44f971b/Mentor-Connect-Facilitating-Meaningful-Professional-and-Academic-Guidance-Through-a-Digital-Platform.pdf
Agyemang, G., Antwi, H., & Boateng, R. (2024). Enhancing mentorship through technology: A comprehensive review of current practices and future directions [Working paper]. SSRN. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5070036
Succi, M. D., Ghoshal, S., Cheng, D., Alvarez, C., & Bredella, M. A. (2023). A scalable mentoring web platform deployed in a large academic system: Pilot implementation. Journal of the American College of Radiology, 20(4), 502–505. https://www.jacr.org/article/S1546-1440(23)00263-6/abstract
Abhari, K., Williams, D., Pawar, P., & Panjwani, K. (2021). Smart entrepreneurial systems: An application of deep reinforcement learning in improving entrepreneurship mentorship. In K. Arai (Ed.), Advances in information and communication (FICC 2021) (pp. 462–476). Springer. https://doi.org/10.1007/978-3-030-73103-8_33
Singh, H. P., Singh, N., Mishra, A., Sen, S. K., Swarnkar, M., & Pandey, D. (2024). Logistic regression based sentiment analysis system: Rectify. In Proceedings of the 2024 IEEE International Conference on Big Data & Machine Learning (ICBDML) (pp. 186–191). IEEE. https://doi.org/10.1109/ICBDML60909.2024.10577296
Negi, A., Verma, C. V., & Tayyebi, Y. (2024). Artificial Intelligence Empowered Language Models: A Review. In Advances in Data-Driven Computing and Intelligent Systems (pp. 467–479). Springer. https://www.researchgate.net/publication/378484507_Artificial_Intelligence_Empowered_Language_Mo dels_A_Review
Vijayalakshmi, B., Geetha, P., Vijayalakshmi, K., Rekha, M., &Manasa, M. (2021). Integrated Digital Mentor-Mentee Interaction Platform. Department of Computer Science and Engineering, Narayana Engineering College, Nellore, Andhra Pradesh, India. https://www.jetir.org/view?paper=JETIRGJ06008
K S, A., M, A., H, D., Anusha, & S, S. (2018). Automated mentoring system. International Journal of Engineering Research in Computer Science and Engineering, 5(4), 496–501. https://www.technoarete.org/common_abstract/pdf/IJERCSE/v5/i4/Ext_86351.pdf
Sheeba, L., &Selvanayaki, M. (2021). Online Student Mentoring System. Turkish Journal of Computer and Mathematics Education, 12(14), 1319–1324. https://turcomat.org/index.php/turkbilmat/article/download/10441/7871/18593
Kram, K. E. (1985). Mentoring at work: Developmental relationships in organizational life. Glenview, IL: Scott Foresman. https://www.researchgate.net/publication/232463073_Mentoring_at_Work_Developmental_Relationships
_in_Organisational_Life
Higgins, M. C., &Kram, K. E. (2001). Reconceptualizing mentoring at work: A developmental network perspective. Academy of Management Review, 26(2), 264–288. https://www.researchgate.net/publication/234021596_Reconceptualizing_Mentoring_at_Work_A_Develo pmental_Network_Perspective
Eby, L. T., Allen, T. D., Evans, S. C., Ng, T., & DuBois, D. (2007). Does mentoring matter? A multidisciplinary metaanalysis comparing mentored and non-mentored individuals. Journal of Vocational Behavior, 72(2), 254–267. https://pmc.ncbi.nlm.nih.gov/articles/PMC2352144/
Crisp, G., & Cruz, I. (2009). Mentoring college students: A critical review of the literature between 1990 and 2007. Research in Higher Education, 50(6), 525–545. https://link.springer.com/article/10.1007/s11162-009-9130-2
Masudi, M. (2024, July 19). Student retention: 5 effective solutions that will work for tutoring businesses. Wise.
https://www.wise.live/blog/student-retention-how-to-solve/#:~:text=Ensure%20that%20your%20LMS%2 0supports,to%20address%20any%20discrepancies%20and
Prakash, S., Dhaksinyaa, M. D., Jothiga, S., Gayathri, G., & Elakkiya, M. (2025). ALGO MENTOR AI– A bipartite matching system using supervised learning. International Journal of Research Publication and Reviews, 6(5), 4293–4298. https://ijrpr.com/uploads/V6ISSUE5/IJRPR45155.pdf
McGuire, M. (2024, February 6). How to evaluate mentorship platforms. GrowthMentor. https://www.growthmentor.com/blog/how-to-evaluate-mentorship-platforms/
Alhassan, I., & Jamil, N. (2021). Sentiment analysis of students’ feedback with NLP and deep learning: A systematic mapping study. Applied Sciences, 11(9), 3986.
https://www.mdpi.com/2076-3417/11/9/3986#:~:text=Students%E2%80%99%20feedback%20is%20an% 20effective,with%20the%20comments%20of%20students
Solipuram, M. (2024, September 30). Application of LLMs to pairing use cases: Mentor and mentee matching. Medium.
https://medium.com/@manishasolipuram/application-of-llms-to-pairing-use-cases-mentor-and-mentee-m atching-5022c7f67552
Kumar, C. V. (2025, May 9). Site architecture and system design for an e-learning platform. FastPix. https://www.fastpix.io/blog/site-architecture-and-system-design-for-an-e-learning-platform
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