Train Your Real Estate Firm to Automate Repetitive Work With AI

Mostly for the work that repeats: pulling data out of rent rolls, T12 statements and offering memorandums, entering property manager reports, building the same comparisons every month, and answering routine applicant and resident questions. These tasks follow the same steps each time, which is what AI handles well. Pricing a deal and deciding whether to buy it stay with people.

Start with the task your team repeats most. For investors that is usually getting rent roll and T12 data into the underwriting model, or entering monthly property reports and comparing them. For brokers it is usually the rent roll, T12 and unit mix summaries in an offering memorandum. All of these are high-volume, follow clear rules and are easy to check.

No. It takes over data entry and formatting so your people can spend their time on judgment, relationships and decisions. The point is to give the same team more time for the work only they can do.

Yes. The rent roll, T12 and unit mix summaries in an offering memorandum can be produced automatically from the property's documents, so the team spends its time on the story and the pricing.

Yes. We set up chatbots that answer applicant and resident questions at any hour of the day, so nobody waits for the office to open.

Usually not. Most automations can be built with Claude or ChatGPT and connected to what you already use: Excel, your database, email and shared drives.

We look at how each department works, pick the repetitive tasks worth automating, build the automations inside your existing workflow, and train each department to build and maintain its own.

We don't deliver a black box. Most automations are built in plain English with tools like Claude and ChatGPT, and we teach your team how they work so you can change them and build new ones without us.

It depends on the task. Some jobs are handled well by a tool you can buy today. Others are a better fit, and cheaper, when your team builds the workflow in house with Claude or ChatGPT. We compare the two with you for each task, so you don't pay for software you could have built, or build something you could have bought.

No. If someone can describe a task clearly in plain English, they can learn to automate it. We step in ourselves when a workflow needs a more difficult integration.

Investors, lenders and brokers in every property type, including multifamily, office, industrial and retail, along with the property operations teams that support them. Inside a firm, any department with work that repeats is a candidate.

It depends on how many departments and workflows are involved. Schedule a call and we will scope it with you.

It is a 20-minute call with David Bratslavsky, QuickData's founder. Bring one task your team repeats every week or month. On the call we show you how it gets automated and how your team can own it afterwards.

David Bratslavsky is the founder of QuickData.ai. He is a multifamily investor who has underwritten deals himself and has spent more than a decade building software, including as a CTO. He consults with commercial real estate investors, lenders and brokers on putting AI to work in their own operations.

Yes. Drop a multifamily rent roll or T12 into the upload box on this page, or run one of the samples, and you will see the result right away.

Excel (xlsx, xls), CSV and PDF, exported from any property management system, including Yardi, RealPage, Entrata, AppFolio, ResMan and MRI.

Your first 20 documents are free. After that it is $99 a month for each person on your team: you add and remove people as you go, and an invitation costs nothing until it is accepted. A credit card is required to sign up, and billing starts only after your first 20 documents.

Rent roll data extraction, also called rent roll parsing, means reading a rent roll file and turning it into structured data: one row per unit with its unit type, resident, lease dates, rents and charges. QuickData does this for multifamily rent rolls in Excel, CSV and PDF and checks the result against the totals the document prints.

Drop the PDF into the extractor. It reads the layout, returns every unit as a row with the same column names each time, and flags anything that does not reconcile with the document's own totals. With the Excel add-in the rows land directly in your underwriting model.

Upload the rent roll and the extractor returns one row per unit, with unit type, square feet, resident, lease dates, market rent, in-place rent and every other charge, plus a unit mix summary. With the Excel add-in the data lands in your workbook.

A T12 (trailing twelve months) is a property's monthly income and expense statement for the last year. The extractor reads the 12 months, puts every line into a standard category such as Gross Potential Rent, Utilities or Repairs & Maintenance, and checks the result against the statement's own income, expense and NOI totals.

Yes. Rent roll and T12 data can be placed into any Excel underwriting model, including your firm's own template.

99.3% accurate. Every document goes through several stages of validation against its own printed totals. When a figure doesn't reconcile, the result is marked for review and tells you what to look at.

Yes. Add your own categories under any standard one, for example Electricity and Gas under Utilities, and matching lines are sorted into them automatically.

It is built and tested for multifamily rent rolls and T12 operating statements. If you need other document types automated, schedule a call and we will look at it with you.

Your file is read to produce your result, and QuickData stores nothing of it when it reads cleanly: not the file, not the result. A file that can't be read, or whose result needs review, is saved as an anonymized copy (residents' names, ids, emails and phone numbers replaced) so our team can fix the cause; it is deleted when that is done, and after 30 days at the latest. Your data is never sold or shared with marketers. Text from it goes to our AI processing providers to help read it, and neither may train on it: one reads every document and keeps nothing, and the other checks some documents when the first is unsure or the result doesn't match the document's totals, and deletes what it receives within 30 days. Details are in our privacy policy.

Standardized JSON. A multifamily rent roll comes back as one object per unit with the same field names every time, plus a unit mix summary. A T12 comes back as categorized monthly line items, each with its twelve monthly values and the total the statement prints. Both include a report that says whether the result matched the document's own totals.

No. Send any file to one endpoint and it works out whether it is a rent roll or a T12.

Excel (xlsx, xls), CSV and PDF, up to 25 MB, from Yardi, RealPage, Entrata, AppFolio and other property management systems. Every source comes back in the same schema, so you write your integration once.

Your first 20 documents are free. After that it is $99 a month for 100 documents, and $1 per document after that. A credit card is required to sign up, and billing starts only after your first 20 documents.

No. A file that can't be read is not billed. Every document that is read is counted.

Each result is compared with the totals the document prints. It comes back marked ok or needs review, with the reason, so your code can decide what to do with it.

Yes. You can call the same extraction from Claude, ChatGPT or your own AI agent, on the same account.

Developers at companies with their own software or database, and commercial real estate software providers that want tested rent roll and T12 extraction in their own product instead of building and maintaining it themselves.