Rake ML

Rob Nielsen

Rob Nielsen is an Executive Vice President at JLL, specializing in tenant representation for locally headquartered office tenants across the Puget Sound region. With over 18 years of dedicated experience, Rob provides expert guidance on lease renewals, expansions, and relocations, often assisting companies managing complex portfolios of leased and owned office spaces.

Kevin Kabaria is Co-Founder and CTO of RAKE ML, with a background in AI for asset intelligence. He previously served as a Senior Software Engineer at Bloomberg LP and is a Princeton University graduate, contributing deep technical expertise to the startup.

Rafael Ortega is Co-Founder and CEO of RAKE ML, with expertise in AI for property damage assessment and over a decade of leadership in naval aviation. He holds an MBA from Chicago Booth and a BS in Economics from the U.S. Naval Academy.

Commercial real estate is under pressure

For nearly two decades, property management has relied on two main tools for operational excellence: the seasoned intuition of veteran operators and the digital dashboards of the information technology era. But with portfolios aging and costs soaring - insurance up 30% each year, materials up 35%, reactive repairs costing 4x planned work - the traditional playbook is no longer enough. Owners and operators are pressured from all sides: physical assets are deteriorating, financial statements are absorbing volatility at the cost of reduced profit margins, and tenants are demanding reliability, but are too often faced with unplanned pass-through charges for capital expenses. Property owners need intelligence that shows not just what is happening, but why, so that they can make informed decisions faster and more effectively.

Causation is the new breakthrough in CRE

The established tools such as sensors and dashboards track everything but explain nothing. We know a roof is running hot but not why it matters - is action required now to prevent a costly failure in the future?

Enter reasoning AI, a new technological development that, unlike previous predictive tools that simply project data, has the power to understand why - It connects the chain of cause and effect. Reasoning AI understands how membrane aging accelerates when water ponding combines with freeze-thaw. It understands how a neglected drain shortens service life and raises the risk of a leak during a storm. Prediction gives you timeline windows; reasoning AI tells you why, when, and, most importantly, what to do next.

"Large scale property owners are trying to find meaningful, high impact ways to adopt AI and the reality is the business case is finally becoming clear from the massive expense mitigation and management opportunity that reasoning AI is providing the CRE industry.​"

The application is practical. For example, a reasoning AI model can identify roof sections under compound risk from drainage, weather, and materials, and then simulate interventions. It can show that re-coating properties this fall prevents five full replacements next year, thus preserving capital and avoiding tenant disruptions. It can even reveal non-obvious efficiency improvements, such as staggering repairs to match contract availability and lead times. This way, decisions move from reactive to proactive.

Reasoning AI generates further operational benefits. Bundling projects that share a common degradation timeline cutting procurement costs by 15 to 20 percent. Smarter scheduling of repairs avoids warranty disputes. Work orders shrink because nuisance alarms no longer trigger unnecessary calls. Consequently, tenants experience fewer disruptions while owners meet sustainability targets. 

The financial impact is transformative. Finance teams now gain control of vital decision intelligence. Capital plans can be laddered to protect key metrics ahead of a refinance, accelerating critical work and confidently deferring non-critical spending. In insurance negotiations, this moves the conversation from promises to proof, demonstrating a clear, reasoning-driven pathway to resilience.

This is not about more data but better thinking with the data already in place. Reasoning AI scales the expertise of a portfolio’s best operators across every asset and crystallizes complex interactions into actionable insights.

Does this sound like science fiction? It is not. This technology is out there and available. Commercial real estate has historically been slow to change, but CRE investors and stakeholders, many of whom are embracing AI in other parts of their investment portfolios, no longer want the “Because we’ve always done it this way” response to capital expense planning. Large scale property owners are trying to find meaningful, high impact ways to adopt AI. The reality is the business case is finally becoming clear from the massive expense mitigation and management opportunity that reasoning AI provides the CRE industry. Some large property owners will keep doing things the way they have always done them, but for the ones that are willing to embrace emerging, focused technology they will be rewarded with fewer surprises, improved margins, and more satisfied tenants.