In a fast-paced Agile work environment, scrum meetings are organized to maximize efficiency. However, meetings that are supposed to last less than 15 minutes can often drag on for much longer, consequently draining valuable time.

What it does

Kong is a voice-enabled project management assistant. It acts as the voice-automated scrum master by leading the daily meeting in a concise, efficient and logical manner. Furthermore, it dynamically modifies tasks by connecting to an Agile project management software maintained through the cloud.

How we built it

Using Google Cloud Natural Languages API, our team built a program that transcribes the users' speech to text, converts text to JSON commands, and finally transforms JSON commands into information that you see on the screen. Ultimately, Kong can filter through the noise to collect the most relevant data to be transformed into instantaneous updates for users enrolled in the project to view on their personal devices.

Challenges we ran into

Our team had to pivot many times when we realized that certain frameworks we wanted to work with were not compatible for the ideas that we had planned with the time frame we were working with. For example, SOX, the Google Cloud Speech-to-Text API and the Google Cloud Natural Language Syntax API were used instead of DialogFlow.

In addition, every single person purposely decided to tackle new challenges. Individuals who had little experience with coding attempted to learn front-end design through React. Meanwhile, those who have built projects using React in the past looked towards back-end development using Firebase. Moreover, all of our members ventured into voice-enabled technology for the first time.

Accomplishments that we're proud of

We are most proud of our willingness to take risks and try new challenges. When obstacles were encountered, we relied on each other for expertise outside of our own familiar domain. Challenges and teamwork inspired us to not only improve the product but ourselves as well.

What we learned

Within these 36 hours, we obtained the fundamental knowledge of new technologies even if they were not all applied n the final product (e.g. CSS, HTML, JavaScript, Express, Python, Google Cloud API, DialogFlow, Twilio, etc.). In addition, we learned how to quickly find reliable and comprehensive resources. More over, we learned to use our network and reach out for help from the right people.

What's next for Kong

Some possible next steps for Kong is to find a way to export the information through APIs. Additionally, our team could reduce the response time and expand the length of the recording. We may also expand our software to support voice recognition for individual users and delve into integration with personal notification systems (e.g. google calendars). Finally, it should be a long term goal to improve the security and storage of Kong.

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