Keyway
Extracts structured data from unstructured CRE documents and generates AI-driven rent comps using public data and tenant sentiment, primarily for multifamily underwriting teams.
Last reviewed 6/2/26
How Keyway uses AI[1][2][3]
AI reads unstructured real estate documents and public listing data to automate underwriting, document abstraction, and rent comps for multifamily investors.
- • Document type detection across loans, leases, OMs, rent rolls, and T12s
- • Field extraction into custom abstract templates, exported to Excel or BI tools
- • Rent comps built from scraped, normalized public listing data
- • Predictive pricing forecasts for acquisitions
- • Listing-photo analysis to flag renovations and property quality
- • Tenant sentiment summarized from online reviews
AI type: LLM
What it helps you do
Built for
Key numbers
- • $400M+ in CRE assets facilitated
- • 50% lower transaction fees
- • 90% faster transaction time (self-reported)
- • SOC 2 Type II certified
Credibility
- Founders & team
- Matias Recchia (CEO, ex-founder IguanaFix for JLL/CBRE, ex-McKinsey) and Sebastian Wilner (COO, ex-Google ML engineering lead)
- Customers
- Blackstone, Brookfield, Goldman Sachs, Starwood Capital Group
- Investors
- Canvas Ventures, Camber Creek (led Series A), FJ Labs, Crosscut, Thomvest. $45M+ total equity raised.
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