This project was developed with the RBC challenge in mind of developing the Help Desk of the future.

## What inspired us

We were inspired by our motivation to improve the world of work.

## Background

If we want technical support, we usually contact companies by phone, which is slow and painful for both users and technical support agents, especially when questions are obvious. Our solution is an online chat that responds to people immediately using our own bank of answers. This is a portable and a scalable solution.

## Try it!

<http://www.rbcH.tech>

## What we learned

Using NLP, dealing with devilish CORS, implementing docker successfully, struggling with Kubernetes.

## How we built

* Node.js for our servers (one server for our webapp, one for BotFront)
* React for our front-end
* Rasa-based Botfront, which is the REST API we are calling for each user interaction
* We wrote our own Botfront database during the last day and night

## Our philosophy for delivery

Hack, hack, hack until it works. Léonard was our webapp and backend expert, François built the DevOps side of things and Han solidified the front end and Antoine wrote + tested the data for NLP.

## Challenges we faced

Learning brand new technologies is sometimes difficult! Kubernetes (and CORS brought us some painful pain... and new skills and confidence.

## Our code

<https://github.com/ntnco/mchacks/>

## Our training data

<https://github.com/lool01/mchack-training-data>
## Inspiration

Cliff is dyslexic, so reading is difficult and slow for him and makes school really difficult.
But, he loves books and listens to 100+ audiobooks/yr. However, most books don't have an audiobook, especially not textbooks for schools, and articles that are passed out in class. This is an issue not only for the 160M people in the developed world with dyslexia but also for the 250M people with low vision acuity.
After moving to the U.S. at age 13, Cliff also needed something to help him translate assignments he didn't understand in school.
Most people become nearsighted as they get older, but often don't have their glasses with them. This makes it hard to read forms when needed. Being able to listen instead of reading is a really effective solution here.

## What it does

Audiobook maker allows a user to scan a physical book with their phone to produced a digital copy that can be played as an audiobook instantaneously in whatever language they choose. It also lets you read the book with text at whatever size you like to help people who have low vision acuity or are missing their glasses.

## How we built it

In Swift and iOS using Google ML and a few clever algorithms we developed to produce high-quality scanning, and high quality reading with low processing time.

## Challenges we ran into

We had to redesign a lot of the features to make the app user experience flow well and to allow the processing to happen fast enough.

## Accomplishments that we're proud of

We reduced the time it took to scan a book by 15X after one design iteration and reduced the processing time it took to OCR (Optical Character Recognition) the book from an hour plus, to instantaneously using an algorithm we built.
We allow the user to have audiobooks on their phone, in multiple languages, that take up virtually no space on the phone.

## What we learned

How to work with Google ML, how to work around OCR processing time. How to suffer through git Xcode Storyboard merge conflicts, how to use Amazon's AWS/Alexa's machine learning platform.

## What's next for Audiobook Maker

Deployment and use across the world by people who have Dyslexia or Low vision acuity, who are learning a new language or who just don't have their reading glasses but still want to function. We envision our app being used primarily for education in schools - specifically schools that have low-income populations who can't afford to buy multiple of books or audiobooks in multiple languages and formats.

## Treehack themes

treehacks education Verticle > personalization > learning styles (build a learning platform, tailored to the learning styles of auditory learners) - I'm an auditory learner, I've dreamed a tool like this since the time I was 8 years old and struggling to learn to read. I'm so excited that now it exists and every student with dyslexia or a learning difference will have access to it.

treehacks education Verticle > personalization > multilingual education ( English as a second-language students often get overlooked, Are there ways to leverage technology to create more open, multilingual classrooms?) Our software allows any book to become polylingual.

treehacks education Verticle > accessibility > refugee education (What are ways technology can be used to bring content and make education accessible to refugees? How can we make the transition to education in a new country smoother?) - Make it so they can listen to material in their mother tongue if needed. or have a voice read along with them in English. Make it so that they can carry their books wherever they go by scanning a book once and then having it for life.

treehacks education Verticle >language & literacy > mobile apps for English literacy (How can you build mobile apps to increase English fluency and literacy amongst students and adults?) -One of the best ways to learn how to read is to listen to someone else doing it and to follow yourself. Audiobook maker lets you do that. From a practical perspective - learning how to read is hard and it is difficult for an adult learning a new language to achieve proficiency and a high reading speed. To bridge that gap Audiobook Maker makes sure that every person can and understand and learn from any text they encounter.

treehacks education Verticle >language & literacy > in-person learning (many people want to learn second languages) - Audiobook maker allows users to live in a foreign countrys and understand more of what is going on. It allows users to challenge themselves to read or listen to more of their daily work in the language they are trying to learn, and it can help users understand while they studying a foreign language in the case that the meaning of text in a book or elsewhere is not clear.

We worked a lot with Google ML and Amazon AWS.
## Inspiration

One thing the pandemic has taught us was the severity of mental health and how crucial it is to have someone to talk to during hardships. We believe in using technology to create a solution that addresses mental health, a global issue of utmost importance in today's world. As high school students, we constantly face stress and emotional challenges that significantly impact our lives. We often want help to get out of a hard situation, however; the help we receive, such as a therapist and a list of non-profit help lines, isn't usually the help that we want such as someone to talk to.

## What it does

My-AI is a chatbox that has a one-on-one conversation with the user in a way that is comforting and helpful by providing emotional support and advice. Maiya, the AI chatbot, assesses the user's messages and feelings to generate a human-like response so the user feels as if they are talking to another human, more so to a friend; a friend without bias and judgement. The entire conversation is not saved and so deleted once the user finishes the conversation.

## How we built it

We prototyped on Figma and then developed the front end with React. Our backend was created using Java Script to made the node server, which is responsible for calling the API.

## Challenges we ran into

Our team ran into many problems as it was one of the first hackathons that most of our team members attended. In terms of front-end development, none of our team members had experience in React so building a website within a time constraint was a learning curve. Other problems we faced in the backend were issues with the API as it would not respond sometimes, the accuracy was off, and wasn't doing what we needed it to do. Finally, we had trouble connecting the back end to the front end.

## Accomplishments that we're proud of

One thing our whole team is most proud of is our skillset improvement in React. All members experienced using React for the first time so navigating an issue for us helped us grasp a better understanding of it. We are also extremely proud of the fine-tuning of the API to meet our project's demands.

## What we learned

We mainly enhanced our skills in React and how to implement and fine-time an API.

## What's next for My-AI

The more Maya is trained with people and different experiences obtained through the chat box, the more accurate the support is.