AI in Real Estate is the intersection of the world’s largest asset class and the world’s most powerful technology, yet most people do not use it correctly.

The core advantage isn’t a legacy LLM where you copy and paste a prompt, it’s a multi-layered orchestration system in which LLMs coordinate deterministic routes over a company’s own ontology and concatenated data, so workflows run end to end with accuracy, memory, and auditability.

In other words, it algorithmically performs the same tasks as your employees but at machine speed and with more context on your proprietary data, leading to a greater and more accurate end result. This allows firms to scale and close more deals without adding headcount–or, as I believe is more likely across the industry, to scale and add headcount.

The second-order consequence of this newfound ability to scale is an increase in aggregate demand for good employees, rather than employing AI-powered operating systems as a replacement for employees. The reality is that, as a business owner, you’d like as many people as possible leveraging this powerful technology—technology that through its use, increases your ability to generate revenue and achieve alpha.

As time goes on, more and more commercial real estate companies will converge on this paradigm and will shy away from disparate AI tools and platforms that withhold access to their own data collection and that don’t mold perfectly to their own ontology.

The images below show one of our clients and the data they’ve collected over the last two days from using their AI-powered operating system.

In the zoomed-in image, the circles are objects like underwriting models/model cells, leases, tenants, clauses, OMs, rent rolls, T-12s, etc.; the lines represent the referencing and usage of those objects. This is the visual representation of a CRE company automating things like financial analysis/modeling, legal document generation, research & reporting, OM, T12, rent roll, zoning, etc. document abstraction & enrichment.