Winner - 3rd Place - 2024 Seneca Housing Hackathon

My Role
As the sole designer on my team, my role extended to all areas of the proposal. I conducted user research, worked on idea development, and iterating and creating the working prototype.

Platform
Website

Sector
Housing

Duration
Approx 48 hours

Team
4 members

Tools
Figma
Photoshop

The challenge

So how’d we do?

Over the course of the hackathon, we were charged with creating housing tech in response to the current pressing challenges of Canada's housing crisis.

Our project was chosen as one of the Top 4 by the judges out of 1000+ participants.

After a final pitch and round of voting with all participating teams, we successfully took home the 3rd place prize!

LeaseLens

Introducing LeaseLens, an online platform where landlords and tenants can read and understand what they’re rental agreements and contracts are really saying.

Explore the final prototype here 👇

Canada’s Housing Challenge

Research

The challenge of affordable housing is a big one, and our team understood that whatever solution we designed wouldn’t be able to tackle all facets of this large crisis.

Drawing from our own experiences as young individuals renting in an unaffordable housing market, we decided to focus our research on the challenges with relation to renting to limit our scope.

What did we find?

In looking at the problem space online, and in forums like reddit, we discovered that landlords and tenants often face challenges related to leases and rental agreements due to a variety of problems.

  • When landlords have ambiguous language in their clauses, it sets the stage for possible exploits from the tenants using loopholes to their advantage.

  • Canada consists of a large and growing community of immigrants. Language barriers made it harder for individuals to lease and rent property.

  • Some landlords create contracts that enforce policies that are not legally binding and rely on the tenant's lack of information on the subject, resulting in tenants understand recommendations as legally enforceable clauses.

Therefore we asked ourselves:

How can we help potential tenants verify their leasing agreements and help them understand what they are signing? 

How can we help homeowners create a tailored leasing agreement without legal knowledge? 

User Personas

Who are the users?

Hence from our work there are two potential users:

  • the tenant

  • the landlord

LeaseLens

From our research and understanding of challenges, our team envisioned a platform where both tenants and landlords could easily understand what their rental contracts were really saying. We coined this online platform - LeaseLens.

As the sole designer of our interdisciplinary item, I individually developed, prototyped and tested the solution.

We brainstormed together multiple ideas, but focused on implementing a couple key ideas that would have the greatest impact.

Analyze

Offer analyses, identification of infractions and suggestions on rental agreements.

Translate

Offer a translation tool to help simplify language and help English as a second language users.

Collaborate

Allow for collaboration and contribution on the platform between tenant and landlords.

Edit

Allow users to edit, markup and comment on their documents.

Here’s how we implemented these ideas 👇

Home page

Form Landing Page

Information Page

Tenant/Landlord Landing

Tenant/Landlord Review Page

Collaboration Pop-up

Wireframing

An iterative Process

Between the qualifier submission and the final hack day, we made some iterative refinements to the prototype, addressing a few key pain points:

  • Initially the landlord and tenant UI were similar but had different functions. We realized that the tools offered to one, should in fact be offered to the other.

  • Better text to white space ratio and clarity of language

  • We also introduced a collaboration feature we weren’t able to incorporate early on.

Initial Lo-Fi wireframes and user flow

Ideation

The Tech and Operational side of things

Our team also analyzed the technical, operational and economic feasibility of the solution.

Without getting into too deep into the nitty gritty:

  • LeaseLens incorporates and uses industry standard models like NLP and ML.

  • The UI uses React.js and Redux, and at the backend using Express.js, BERT/GPT, and custom NLP Models

We also developped a business proposal and project roadmap should LeaseLens be realized.

Through our pitch and mentoring sessions with the judges, we received feedback that helped us think beyond our boundaries.

Some things we could have done if we had more time:

  • usability testing

  • developing a mobile version - we thought an ability for users to scan the documents using their mobile on the go would be an important feature moving forward.

Lessons Learned

There is great power in collaboration. As a diverse team of different skillsets, I believe our different backgrounds, skills, and opinions contributed to the development of our design that led to our eventual win.

Acknowledgement: Vector illustrations used in this project are from UnDraw.