Inspiration
Having experienced a language barrier firsthand, witnessing its effects in family, and reflecting on equity in services inspired our team to create a resource to help Canadian newcomers navigate their new home.
Newt aims to reduce one of the most stressful aspects of the immigrant experience by promoting more equitable access to services.
What it does
We believe that everyone deserves equal access to health, financial, legal, and other services. Newt displays ratings on how well businesses can accommodate a user's first language, allowing newcomers to make more informed choices based on their needs.
When searching for a particular services, we use a map to display several options and their ratings for the user's first language. Users can then contact businesses by writing a message in their language of choice. Newt automatically translates the message and sends a text to the business provider containing the original and translated message as well as the user's contact information and preferred language of correspondence.
How we built it
Frontend: React, Typescript
Backend: Python, Flask, PostgreSQL, Infobip API, Yelp API, Google Translate, Docker
Challenges we ran into
Representing location data within our relational database was challenging. It would not be feasible to store every possible location that users might search for within the database. We needed to find a balance between sourcing data from the Yelp API and updating the database using the results without creating unnecessary duplicates.
What we learned
We learned to display location data through an interactive map. To do so, we learned about react-leaflet to embed maps on React webpages. In the backend, we learned to use Infobip by reviewing related documentation, experimenting with test data, and with the help of Hack Western's sponsors. Lastly, we challenged ourselves to write unit tests for our backend functions and integrate testing within GitHub Actions to ensure every code contribution was safe.
What's next for Newts
- Further support for translating the frontend display in each user's first language.
- Expanding backend data sources beyond the Yelp API and including other data sources more specific to user queries


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