Developer Spotlight: Team Sign-off

Spotlight Developer, Team Sign-off

This month for our developer spotlight, we wanted to highlight members of another amazing winning hackathon team that featured the DocuSign eSignature API. The team, called Sign-off, won our $2K HackMIT challenge of the Best Use of the DocuSign eSignature API.

Sign-off is a web application tool that aims to ease the process of business contract signing by reducing human error. Their tool presents the user with summarized document text by using fundamentals of natural language processing (NLP). It does this by ensuring that all key points in the contract are presented to the user. The summarized text is passed through DocuSign's eSignature API to the recipient, along with the link to contract to be signed. The sender is notified when the recipient signs the document through our web application tool. Team Sign-off got their inspiration for the project when they determined that people don’t like to read long documents and wanted to incorporate NLP to solve this problem.

 

Nandit Mehra – Nandit is a final year computer science student from India. He has interests in machine learning, natural language processing, and web development. Nandit loves to work on ideas that tend to impact the lives of the masses. He is also fascinated with meeting new people and discussing new ideas and technologies. Nandit loves to play chess and to learn about blockchain. He also has a passion in learning new languages (with Mandarin in progress). You can contact Nandit on Twitter, LinkedIn, and GitHub.

 

Harsh Patel – Harsh is a senior from Boston University, majoring in Computer Science with a minor in business. His passion for technology and entrepreneurship has helped him solve inefficiencies within Fortune 500 companies such as Boeing and Philips. He finds himself traveling across the world to attend hackathons and incorporate API's such as DocuSign’s. He loves to mentor, coach, and inspire others in the areas of programming and business development. His origins lie from a small village in India, so he’s proud to be a first-generation college student and the son of two hard-working immigrant parents. Throughout his life, he’s learned how to put smiles on faces and to never stop growing! You can reach Harsh on LinkedIn.

 

Regina Lyons – Regina is a senior at Rutgers University, studying Mechanical Engineering. At Rutgers, she is an active sister of Omega Phi Alpha, member of SWE, cofounder of Connecting Girls to Mechanical Engineering, and she plays club lacrosse. Regina loves to learn and try new things. In her free time, she like to workout at the gym and hang out with friends. When she’s home from school, she enjoys spending quality time with her grandpa, who's her role model. She plans on working after graduation in May and is currently exploring career paths in both mechanical engineering and software development. After graduating and before starting work, she wants to travel around Europe. She’s always looking for life advice, so feel free to reach out to her on LinkedIn.

 

Robin Lin – Robin is a sophomore at the University of Toronto, majoring in Engineering Science. He is passionate about the application of machine learning in applied physics and he hopes to eventually pursue graduate studies in this field. He is also an IoT and robotics enthusiast. He has created many hackathon and side projects that focus on solving real-life issues via hardware and software. Robin is also passionate about competing in undergraduate and graduate level engineering competitions. He is part of the UofT Self-Driving Car and Humanoid robot teams. His team qualified and competed in the SAE Autodrive challenge in Arizona, as well as the 2018 RoboCup held in Montreal. Robin can be contacted on LinkedIn.

 

If you have deployed solutions using the DocuSign eSignature API and you’d like to be considered for a future Developer Spotlight, please send me an email to tony.mann@docusign.com with information about your solution and a bio.

Tony Mann
Author
Tony Mann
Director of Developer Content
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