Tendir: The Tinder for Business

Graph of tender offers

Inspiration

Our inspiration for the project was the struggle to connect contract workers and publishers in an inefficient tender system. We wanted to create an efficient, more usable alternative.

What it does

Tendir allows the user to sort through tender offers based within a distance from their location. This allows them to quickly find the best offers and sort through them. They can tag offers to further organize them and can view a graph that is sorted by tags and distances. They can also like and dislike tenders to save offers they are considering. This helps combat climate change in a few ways. First, energy usage contributes to 35% of greenhouse gas emissions, and by 2025 40% of energy usage will be from information and communication technology. Tendir was designed to be efficient and precise to avoid wasting and energy and be a much more manageable way to connect contract workers and publishers. Additionally, Tendir is more accessible which will increase both the publishers and contract workers. This will increase competition which will make government projects for climate change to be filled by better applicants.

How we built it

We built the web application primarily with Vue and TypeScript, with HTML and CSS overlayed to create the front end. First we had to sort through json data on tenders. Then, we allowed the user to like or dislike using a Tinder like swipe, sorting the tenders based on what they were interested in. They could tag tenders for further sorting. Then, they could generate graphs based on various attributes to manage the data. We found a force-directed iterative layout to be most effective.

Challenges we ran into

It was a challenge to determine the distances between a set location and the database's information about the address of the publishing contract. Luckily we were able to efficiently allow the user to only get information about tenders within a certain radius using maps. Additionally, creating the graph was very complex as there were many different ways to sort the data. We decided on a multi-layered, force-directed iterative layout that would allow the user to configure the graph as they wanted according to tags or other information. Finally, because of the struggle we experienced in fixing the back end, we were not able to get the frontend to the point we would have liked.