When the AI for CRE Collective recently spent time with Prophia, our co-founder and CEO Cameron Steele gave them a fairly blunt assessment of where commercial real estate technology is headed:
“Lease abstracts are dead.”
A bold statement from a company that has processed hundreds of thousands of commercial real estate documents.
But the point isn't that the information contained in a lease abstract no longer matters. Quite the opposite.
The information matters too much to remain trapped in one.
For decades, lease abstraction solved a very practical problem: commercial leases are long, complicated, and constantly amended. Nobody wants to reread hundreds of pages every time they need to know an expiration date, renewal option, operating expense provision, or tenant right.
So we condensed the document.
That was useful. But it also created another static artifact.
Today, we can do something fundamentally different.
We can transform the complete history of a lease into structured, trusted intelligence—then make that intelligence available wherever and whenever the business needs it.
That distinction is at the heart of the AI for CRE Collective's recent review of Prophia.
Their team saw firsthand what happens when Prophia follows a contractual term across multiple documents to determine its current state, connects every data point back to its source, and then puts that information to work across critical dates, stacking plans, reporting, reconciliation, and AI-powered questions.
The value isn't the abstract. It's what the business can do with the intelligence underneath it.
Consider a simple question:
Which tenants have termination rights over the next five years?
Historically, answering that might mean pulling abstracts, searching spreadsheets, checking Yardi or MRI, reviewing amendments, and potentially reopening the source documents to make sure the answer is still right.
That's not really a data-access problem.
It's a trust problem.
The AI for CRE Collective highlighted several examples that show what happens when the information CRE teams rely on doesn't accurately reflect the underlying agreements: an incorrect lease date that could have cost an owner approximately $1.2 million, an outdated base year creating roughly $200,000 in exposure, and a forgotten agreement that ultimately helped recover approximately $800,000 in back rent.
When the information drives decisions involving revenue, risk, obligations, and asset value, “probably right” isn't particularly useful.
The goal is to create intelligence teams can actually act on—and make the evidence behind that intelligence immediately available when they need to verify it.
There's no longer anything particularly novel about an AI model being able to read a lease.
Upload a PDF to a general-purpose AI tool and it can tell you a lot about what's inside.
The harder problem is creating a reliable understanding of a commercial real estate portfolio when the truth may be distributed across an original lease, five amendments, a commencement letter, a side agreement, and years of subsequent changes.
That requires more than extraction.
It requires understanding the relationship between documents, determining which terms supersede others, normalizing information across assets, validating the resulting data, and maintaining a clear connection back to the governing source.
That's the layer we're building Prophia around.
And as AI becomes more embedded in asset management, that foundation becomes even more important. An AI assistant answering questions, an automated workflow monitoring risk, or an agent performing work is only as valuable as the information underneath it.
This is where we believe CRE software is headed next.
The first generation of technology helped digitize information.
The next helped organize and report on it.
The emerging generation will increasingly act on it.
For Prophia, that evolution is already underway.
Customers can ask questions across their portfolio using Prophia's AI Assistant. They can access Prophia intelligence through tools like Claude and ChatGPT using MCP. Contractual information can power critical-date tracking, stacking plans, portfolio reporting, and reconciliation workflows.
And we're expanding the types of documents Prophia can understand, beginning with loan documents.
These capabilities don't make trusted data less important.
They make it the prerequisite.
The more work we ask AI to perform, the more consequential the underlying context becomes.
The AI for CRE Collective concluded its review by observing that Prophia increasingly looks less like a lease-abstraction product and more like a trusted data layer beneath commercial real estate operations.
That's very close to how we see the opportunity ourselves.
Commercial real estate is governed by documents. Those documents define revenue, obligations, rights, restrictions, debt, risk, and ultimately asset value.
For years, the industry's challenge was extracting that information.
Now the opportunity is putting it to work.
That's why the future of Prophia isn't about producing a better lease abstract.
It's about transforming the documents that govern CRE into trusted intelligence—and using that intelligence to help teams understand risk, surface opportunity, make better decisions, and increasingly automate the work required to manage their assets.
The AI for CRE Collective sat down with Prophia CEO and co-founder Cameron Steele and Jeremy Bergeron for a deeper conversation about how Prophia has evolved, why trusted data matters even more in the age of AI, what “lease abstracts are dead” actually means, and where CRE technology goes from here.
You can also read the AI for CRE Collective's full review of Prophia: “Prophia Review — Turn Leases Into Trusted Data.”