At A Glance:

Capstone Sponsor: NobleReach
Capstone Team Lead: Grayson Lawrence
Capstone Team Members: Brian Bogert, Samir Hossain, and Altan Mitchell
Key Problem: Develop an entrepreneurial talent matching system for NobleReach.
Solution: Reduced matching time by 95% and data scraping time by 98% using the developed matching and tagging system.

The Challenge

MSBA-BA graduate students Brian Bogert, Grayson Lawrence, Samir Hossain, and Altan Mitchell collaborated with Noble Reach to develop an entrepreneurial talent matching system. This system aims to automate the process of matching entrepreneurs with government research projects, significantly reducing the manual work involved. The primary objective was to create an efficient and scalable solution to connect entrepreneurs with opportunities at organizations like the National Science Foundation (NSF) and Defense Advanced Research Projects Agency (DARPA), addressing the current manual and time-consuming matching process.

The Solution

The team developed an automated system that uses Diffbot to scrape entrepreneur and startup data and Lightcast taxonomy to tag skills. The system matches entrepreneurs with projects based on skill overlap, significantly reducing the time required for matching by 95% and the time spent on data scraping by 98%. This process involves dividing the gathered data into categories such as education, employment, and general information, which are then analyzed to generate relevant skill tags. The system integrates with Salesforce to track entrepreneur availability, ensuring accurate and efficient project assignments. Financial benefits include reduced matching time and enhanced scaling capabilities, enabling NobleReach to handle more contracts. Further recommendations included optimizing the code for Salesforce integration and implementing a feedback loop with machine learning to continually improve the matching process.

 

2024 NobleReach Team Public Presentation