Taking in Rate and Stock Options which are correlated via Watson
tl;dr - The challenges workplaces face in employee health and retention, which, by extension, influences productivity.
Everyday, hundreds of thousands of employees struggle to maintain a healthy work life balance. This has adverse effects on their lifestyle; while software engineers are usually pointed towards due to their long hours, this problem extends even as far as the financial industry. We envisioned a software that solves these mental and physical issues by promoting greater well-being in a unique mix of life and work.
What it does
Worklife can be summarized into three core features:
- tracking employee well-being via inference and use of strategically targeted questions and non-intrusive notifications
- provides analytics on data tracked for the employee, and anonymized statistics for the employer, powered via artificial intelligence inference
- boosts workplace productivity by improving employee well-being and work/life balance, which has been scientifically proven to improve employee productivity
How we built it
- Node + express server, MERNN stack on AWS
- IBM Watson for Prior training and Preclassification + Baseline Inference
- Python for data preparation, cleaning
- React Native
Challenges we ran into
- Wireless Connection through firewalls
- Putting multiple ideas through into a product
- Connecting through different Cloud Platforms
Accomplishments that we're proud of
- What we built (web, desktop app, mobile app -- the triforce!)
What we learned
- AI integrations with cloud
What's next for Worklife
Launch into the workplace!