Inspiration

The customer experience is heavily dependent on a personalized and seamless experience. We are inspired by the emerging technological advances and created a demo and a scalable layout using advanced technolgies such as NLP through AWS and Machine Learning all in pursuit of improving the customer experience.

What it does

We are creating a customer service infrastructure incorporating multiple features such as personalized user profiles categorizing issues, ensuring proper tickets get passed directly to subject matter experts in order to cut out the middle man in the process, saving time and money. We have prepared other features such as difficulty ratings of issues for training purposes in order to reduce training costs and create new subject matter experts.

How we built it

We used AWS technolgies such as Lex and Lambda in order to do deep analysis on user inputs to correctly tokenise user inputs and to properly categorize issues. For the front-end, we used a combination of clean and clear User Interface with CSS and HTML along with Javascript and Node.js to connect our front-end to the AWS processing platforms.

Challenges we ran into

This was our first time looking into NLP with AWS and Lambda functions, so the learning curve was fairly high. Despite our numerous setbacks in the beginning we were able to create a proper demo to show off our innovative design. The front-end was hosted on Heroku which was a platform we were not familiar with so many issues were found there. Finally, the connection of the front-end with the back-end was the greatest relief when the chat-bot properly circulated.

Accomplishments that we're proud of

We created a working chat-bot which is able to parse inputs and create unique responses according to the customers issues, creating an incredibly efficient yet simple customer service process.

What we learned

We learned different AWS Technologies along with the many intricacies involved with creating a full stack application. Among the many technologies we integrated were Lex, Lambda, RDS, and Heroku.

What's next for Hotline Ming

The next process will be further fleshing out the idea and creating a more in-depth analytical system for our tickets and recurring problems.

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