Phase 1 cut property review from around 10 hours to 1. Then RE Innovation came back to remove the four hours of manual work still sitting around the auction lifecycle.
This was our second project with RE Innovation.
In Phase 1, we automated property sourcing and used AI for the first review of auction documents. Review time dropped from around 10 hours per property to around one. That solved the original problem.
Then the team started seeing the rest of the workflow more clearly. There were still hours of repetitive work around every auction.
So they came back.
A new property entered the CRM. Then someone had to create the Google Drive folder. Find the location in Google Maps. Organise the files.
After the auction, someone collected the property data and wrote a structured update for the team in Telegram. When the auction was finished, completed deals had to be moved to the archive manually.
None of these tasks required an investment decision. But together, they were taking around four hours every day.
Property setup was manual. Drive folders, locations and files were prepared by hand.
Post-auction updates took time. Someone had to collect the data and write the Telegram summary.
Archiving still depended on people. Completed auctions were moved manually.
The team was making decisions faster. Routine work was still following every decision around.
We already had the core system from Phase 1. Properties were entering the CRM and the document review process was working.
The next question was simpler. What still happens every time a property moves through an auction?
Create a folder. Pull the location. Prepare the update. Notify the team. Archive the finished auction.
The pattern repeated every time. And almost none of it needed a person to make a decision.
That made the next automation much more obvious.
When a new property enters the Airtable database, the workflow starts automatically. The system pulls the property location through the Maps API and creates a structured Google Drive folder for the photos and documents.
After an auction, Gemini uses the collected property data to prepare a structured summary. A Telegram bot posts that update directly to the team's channel. When the deal is closed, the property is moved to the archive automatically.
Airtable triggers the process. Maps API pulls the location. Google Drive creates the folder structure. Gemini prepares the summary. Telegram delivers it to the team. Then the record is archived when the work is finished.
The routine steps run in the background. The team handles the decisions.
The system did not replace the team's judgement. It removed the routine work wrapped around it.
Phase 2 removed around four hours of daily setup and reporting work. The auction lifecycle now runs from a new property in the CRM through folder creation, location lookup, post-auction summary, team notification and archiving.
The team receives structured Telegram updates automatically after each auction. Routine work after implementation: zero hours, according to the source case.
The remaining work is the part that needs people.
Decisions.
Same client.
Second project.
Bigger scope.
Show us the full process. The leftover manual work is often easier to see once the main problem is fixed.
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