Automating Real Estate Workflows Webinar

How real estate teams are using AI to move faster

Real-estate teams rarely struggle with judgement. They know when a deal holds up and when it doesn’t. What slows them down is everything that happens before those decisions are made, like documents that arrive in formats no one asked for or data that changes depending on which page you read. Often, an entire afternoon evaporates before any real thinking begins.

That was the starting point of a recent Fifth Dimension webinar, where Ben Schaffer, Growth and GTM, laid out a problem most people in the sector quietly accept. The delay isn’t the analysis as much as it’s the paperwork.

The unseen weight dragging down the top of the funnel

“Teams lose time because nothing comes in a usable shape,” Ben says.

That observation set the tone for the session, which focused less on AI as an abstract idea and more on the basic mechanics of getting work started.

The first saw 14 OMs dropped into Ellie, Fifth Dimension’s real estate AI agent. Teams often end up revisiting the same pages repeatedly before anything coherent emerges. Ellie surfaced two assets that met a stated investment approach without the usual first-round friction.

There was no claim of instant transformation. Ellie stripped away the noise so teams could focus on whether the opportunity deserved legitimate attention.

When diligence is held up by the source material

Ben then moved to diligence, an area that often stalls because the materials contradict each other. One file might be written years before the next, and the numbers inside don’t always align with what they’re meant to support. It only takes a small mismatch to send the team back to the start.

“The issues aren’t hidden,” he said. “They’re just buried under inconsistent paperwork.”

Ellie reviewed a full industrial deal room against a diligence checklist. She picked up the kinds of discrepancies that usually surface late, like a rent figure that didn’t align with the ledger or a financial statement that moved away from its supporting documents. Instead of digging for the starting point, the team was handed one.

Portfolio reviews without the detours

Many of the asset managers watching quickly recognised the next scenario. Quarterly reviews lose momentum when figures shift across documents and the structure around them keeps changing. A review intended to take an hour often becomes an afternoon of resolving which version of a figure is the “real” one.

Ellie processed a four-asset portfolio, and the gaps showed up straight away. One property’s income line didn’t match its rent roll, another showed costs edging higher than expected. A third looked fine until the supporting documents told a different story. The work went from untangling inconsistencies to deciding what the findings meant.

The IC memo without the rebuild

Closing the session was the IC memo, a document few enjoy producing because the materials rarely align. Teams rebuild sections from scratch just to create a version that makes sense.

Ellie drafted a full memo by pulling directly from the OM, the model, and the property reports. Every figure traced back to its source. The value lay in avoiding the cycle of reconstructing something that already exists.

“You still make the decisions,” Ben said. “This just gets you to them faster.”

Why generic AI falls short

Ben returned to one theme throughout – most AI systems struggle in real-estate workflows because they don’t understand why certain documents carry more weight or why inconsistencies cascade. They summarise, but they don’t hold context.

Ellie was built to handle the structure of the work rather than just the text within it, which is why she behaved differently in the examples.

A context-aware assistant for real estate workflows

Ellie gives real-estate teams a clearer starting point. She reads the materials the way the work happens, linking figures back to their sources and showing where the story holds together and where it doesn’t. Instead of wrestling with mismatched documents or rebuilding sections just to make sense of them, teams assess deals with confidence.