Digitaire

Inspiration

The concept of Digitaire originated from a conversation with the vice president of a real estate development company. The words that sparked the birth of the company were “I wish I had…”. Additionally, after working as a leasing consultant and having the exclusive insight in the residential management industry that knowledge greatly influenced the development of the software.

What it does

The company would provide a subscription-based software to landlords and property management teams to help forecast the cost of repairs and replacements for appliances. This will help keep appliances in operation by projecting when preventative maintenance should be made. The software will use AI technology to predict when a certain part will fail, in addition to when and how often a part should be replaced. The company will utilize AWS (Amazon Web Services) as the database to store information to improve the forecasting of the AI. Additionally, DigitAIRE will allow landlords and property managers to document unit inspections and calculate the cost for damages and repairs in real time. Through the use of this technology, facility management is able to better predict their budget and additionally improve the residents' experience.

How will the concept be monetized?

Our Business model consists of creating relations with housing companies to sign residential buildings with our program. We offer services for preventative maintenance specifically for appliances. The way the company generates revenue is through a subscription based service, where the facilities manager can choose to do a monthly or annual contract for our services. The company will provide three tiers of services; with each tier increasing in price and the additional provided services.

Example Case

Landlords and property management are operating estates without knowing the possible expenses they may face in the future. Each apartment or unit of space has appliances such as a dishwasher, refrigerator, washer, and dryer; over time these appliances require maintenance. When an appliance breaks down, residents can be left without that appliance for weeks at a time before the appliance is repaired or replaced. In the event of hose or seal breaks, flooding can occur causing further damage to the appliance and possibly water damage to the apartment. This produces pressure for property management and maintenance to repair the appliance in a timely manner. Property management is then left with the task of calculating the cost of repairs, replacements, and locating materials and parts. One of the examples that best resonates with property owners in the water filter issue. Water filters typically need to be replaced every 6 months. Our company will keep track of all the fridges "deadlines" of when each fridges water filter needs to be replaced. The software will inform property owners ahead of time of when and how many water filters should be ordered for the next month.

Go To Market Strategy

Our go-to-market strategy once we have a Minimally Viable Product is to run a proof of concept (POC) with the building/leasing office that our team member works at and partner with George Mason University for their apartment style housing. We will set benchmarks with our initial customers to understand what results they would like to observe to pay for our services. Once we are able to provide results and establish our credibility, we will expand to the other residential complexes the real estate development company owns.

How we built it

The development of the UX/ UI models of the software were created through Figma. By comparing Digitaire's user interface with other competitors, multiple iterations of the design were done to improve user friendly aspect of the software.

The software will utilize Amazon Web Services (AWS) SageMaker to create, train, and deploy machine-learning models on the cloud.

Challenges we ran into

Obtaining datasets of appliance breakdowns. There can be hundreds of parts that make up an appliance. The solution to this problem is to narrow down the number of components that are being track per appliance to the most common parts that break.

The "ML training" can be greatly screwed based on the customer segment.

Accomplishments that we're proud of

The creation of the UX/UI models. Further understanding of the problem statement and the technologies required to run the software.

What we learned

We discovered that older buildings with aging appliances have larger maintenance costs compared to a unit that may be newly renovated. This directly correlates to a statistic that we found during our market opportunity research that there are 11.7 million older existing apartments that are in need of renovations.

What's next for Digitaire

To understand our prospective clients, our team formulated a survey to capture essential data from property owners/ managers to understand their needs. From the entries of our survey we were able to identify opportunities where property owners can regain capital. This data will allow us to maximize our services for property owners to ultimately save them money.

Built With

• amazon-web-services
• figma
• python
• sagemaker
• tensorflow
• ui/ux