Last year as part of Watsonâ€™s education initiative, 10 U.S. universities taught Watson technology classes. Throughout the semester classes built a live prototype and business case that culminated in a pitch competition at the Watson New York City headquarters in Silicon Alley. The winner, Cerebri, captivated the audience with their social services application that helps citizens quickly gather answers to their most pressing questions. For example, someone could use Cerebri to quickly receive information about the store closest to them that takes food stamps. As part of their win, they received $100,000 in startup funds and also,Â access to the Watson services.Â
We caught up with Cerebri CEO, Ryan Lund and CTO Thejas Prasad to discuss how they are bringing their product to market.
Thejas Prasad: It was an amazing experience for the team. We entered the competition through a University of Texas Austin class. After winning at UT Austin, the team traveled to NYC for the final round. Through the competition Cerebri gained a lot of contacts and network around the Watson platform. This competition gave Cerebri enough seed funding and the boost to incorporate and build a successful startup.Â
IBM Watson Group: Â Which API are you using and how did you land on those?
Ryan Lund: We are currently using the Trade-off Analytics API.Â We chose this solution as it allows us to weigh our customersâ€™ consumer information to get them to the product/service they are looking for.
We are also excited to start using Personality Insights and Natural Language Classifier (NLC) to further this cause.Â Our goal is to use personality insights with other data mining tools to get as much information about the consumer as possible to help drive them to the products/services that other similar customers found useful.Â NLC will allow us to let the consumers use language they are comfortable with to get them started on the custom experience we create for them to find what they are looking for.
IBM Watson Group:Â Â Why is your solution unique?
Ryan Lund: We create a cognitive solution to help community members find services that are available to them without having to call a call center like they used to.Â As we move forward, we continue to use more data mining techniques, NLP and machine learning algorithms, to which Watson is essential, to give the user an even more customized experience and product suggestion.Â Not only that, but the solution constantly â€ślearnsâ€ť and gets better the more it is used!
IBM Watson Group:Â What advice can you give developers who want to build with Watson?
Ryan Lund: Ask a lot of questions and donâ€™t get hooked on one API.Â There are a lot of great APIs and the one you originally look at might not end up being the best fit.
IBM Watson Group:Â How are you implementing your Watson-powered solution with clients?
Ryan Lund: For the Social Services industry, we created a mobile application with a guided search add-on, powered by Watson, to help consumers use their attributes, location and services they are looking for to direct them to the best services available for them.
Now, we continue to expand both in the non-profit and for-profit space with the continual goal to use our products and Watson to drive our customersâ€™ consumers the products they are looking for faster and smarter.Â We know what the consumer is looking for even before they do. And the best part is, the solutions continue to get better over time as they learn consumer behavior.
Put the Watson Developer Cloud to work for you with this case study on usingÂ Natural Language Processing.Â
Read it here.