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Design Tenets: Structuring Data

structuring data with AI

Ender is designed to be your system of record. The current state of the world has notes, spreadsheets, unstructured communication, PDFs, and documents stored in different systems. Yes, we want to centralize all your communication. But just as importantly, we want to structure your data. This enables actionable insight into your organization, empowering your team to make the best decisions for your business.

Unstructured data leads to operational complexity. 

Imagine the basic case of a tenant’s birthday. The tenant’s birthday is written down as a note on their tenant profile. You want to send the tenant a happy birthday message on their birthday and a gift. To do this, you’d have to search every tenant’s profile for their bday. Eventually, you extract the info to a spreadsheet where you arrange it by date and check it everyday to see if it’s a tenant’s bday. The list would need to be updated with new tenants and omit those who move out.

Compare this to Ender that ingests tenant birthdays from the application process. The data is stored in the system, and you make a repeatable task to wish all tenants a happy birthday and send a gift. The software knows which tenants are currently living in the building in which unit. It happens automatically and pops up into a queue of other tasks.

You have a parking lot with assigned spots. License plate numbers are unstructured notes on each tenant’s page. When someone parks in a tenant’s parking space, the PM has to go to each individual tenant page to see if there’s a matching make/model/license plate. One by one the PM clicks through the software to find a matching license plate. When they do, the PM finds the contact details to message them to move their car.

Instead, Ender structures this data. A PM can search the license plate number of the car parked in the wrong spot and immediately see if it’s another tenant in the database. If it’s not in the database, then they can be confident it’s not a tenant and send an announcement to all tenants that they’re going to tow an unregistered car. Search and communication tools streamline this process.

Similarly, structuring renter’s insurance, vendor COIs, and property insurance autocreates tasks for PMs to renew insurance or request updated insurance information before expirations. There are hundreds of workflows like this that go from being tedious to streamlined. Having all the data in one system results in massive efficiency gains.

Tasks are created around a digitized lease. There are numerous provisions that have dates attached to them within leases. This data structuring may cause a bit more work upfront, but it has massive returns. The system will auto-alert you to things going wrong. The same way charge schedules are input, so too can tasks.

Linking tasks and invoices gives insight into how your property is being run. Linking tasks and invoices to the GL gives accountants transparency to easily categorize any line item. Instead of manually charging the excess HOA fee to each tenant, the software can model what percent of the HOA fee each tenant owes and automatically charge them.

With data structured, every property management workflow becomes streamlined and transparent. One can easily answer questions such as: How fast did our PM team respond to issues? How fast did our leasing team respond to inquiries? On average, how many showings until a unit is leased? When are most maintenance requests made? How many HVACs did we fix over the last three years? What were their makes and models?

To streamline accounting, property operations, and leasing workflows, change is needed. These basic process changes pay off quickly.