Commercial real estate runs on judgment and relationships. AI can take the operational weight off — OMs, rent rolls, IC memos, comp pulls, follow-ups — but the read on a sponsor across the table, the trust-building call with an LP, and the discretion to bend a buy-box for the right deal stay with you. We build for that division of labor: AI as the copilot, you as the principal.
The engineering practice is grounded in real research — the AWS AI Research Award for machine learning infrastructure, NSF- funded peer-reviewed work on physics-informed neural networks — paired with operators who have closed $1B+ in CRE transactions and underwritten $11B+ across asset classes. That combination shows up in how the systems ship: explicit uncertainty handling, principled guardrails, and audit trails that hold up under IC scrutiny.
Our conviction is simple. The only people who should be building AI for commercial real estate are people who understand both halves of the problem. Deep AI expertise without institutional CRE experience produces demos that don’t survive IC. Institutional CRE experience without research-grade AI produces faster wrong answers. We sit at the intersection on purpose.