How a Toronto brokerage fills 1,200-field MLS forms and FINTRAC Form 630 in under 2 minutes
A Toronto real estate brokerage, which asked not to be named, handles more than 250 MLS listings and property transactions a year, with one or two clients each week. Every transaction takes 7–15 forms, from MLS® Data Information Forms to the OREA Agreement of Purchase and Sale and FINTRAC identification. With Instafill.ai filling all of them, a form that took 20–40 minutes by hand now takes under 2, and the brokerage saves more than 40 hours a month.
At a glance
- Company Toronto real estate brokerage, under NDA
- Industry Real estate brokerage
- Location Toronto, Canada
- Forms About 15, including MLS Data Information Forms, OREA Form 100 and Form 630
- Volume 250+ listings and transactions a year
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Results
40+ hours saved every month
Under 2 min per form, down from 20–40 minutes
95–97% first-pass accuracy on 1,200-field forms - Catalog forms Form 290, MLS Data Information Form – Freehold Sale, Form 291, MLS Data Information Form – Condo Sale, Form 292, MLS Data Information Form – Condo Lease, Form 296, MLS Data Information Form – Freehold Lease, OREA Form 100, Agreement of Purchase and Sale, Form 630, Individual Identification Information Record
- Form categories OREA forms, Real estate forms
The challenge
The heaviest were the MLS Data Information Forms, one for each type of property: Form 290 for a freehold sale, and Forms 291, 292 and 296 for condo sales, condo leases and freehold leases. Each has more than 1,200 fields: measurements, features, parking, zoning and long runs of checkboxes and dropdowns. Beside them came Form 630 for FINTRAC client identity verification, OREA Form 100, the Agreement of Purchase and Sale, and assignment and amendment forms.
Most of these forms arrived as flat PDFs with nowhere to type, so the team either opened a PDF editor or retyped them in full. The client data was scattered across driver's licenses, property inspection reports, legal descriptions and handwritten notes, and had to be pieced together before any of it went in.
The solution
Instafill.ai's team turned the brokerage's flat forms into fillable PDFs with flat-to-fillable conversion, a one-time step per form that leaves a reusable form behind. They also set up the harder parts of each form: checkboxes, radio buttons, tables and number formatting.
For each transaction, the team pastes the client's details as text, uploads the documents as they are, such as a scanned driver's license or a property record, or uses a previously filled form, as filling sources. Instafill.ai maps the data to each form's fields in 20 seconds to 2 minutes, depending on the form. Repeat clients and the brokerage's own details live in reusable client and company profiles, several clients can come in at once from an Excel spreadsheet through batch filling, and data forwarded by email comes back to the inbox as filled forms.
A broker or the operations lead reviews each filled PDF before it goes out. While the forms were being tested, any field that came out wrong was flagged for correction, and Instafill.ai's team fixed it, typically within 24 business hours.
The results
| By hand | With Instafill.ai | |
|---|---|---|
| Time per form | 20–40 minutes | Under 2 minutes |
| Flat PDFs | Edited or retyped | Converted once, then filled |
| Client documents | Pieced together before entry | Pasted or uploaded as they are |
| Time on forms | 7–15 forms typed per transaction | 40+ hours a month saved |
First-pass accuracy is 95–97%, even on the forms with more than 1,200 fields, so review is short, and when a fix is needed it comes back within 24 hours on business days. Every PDF form the team uses is now in the system with checked field mappings, so each transaction follows the same steps. Getting started took little training.
The brokerage began with the MLS forms, where the hours went, and the simpler forms followed. The setup happened once; every transaction since has used it.
