AI Underwriting Copilot
Turn source documents, explicit assumptions, scenarios, risks, and conditions into a human-owned IC recommendation and maximum acquisition price.
The short answer
Explore the current underwriting workflow →
An AI underwriting copilot is a system that reads a deal's source documents, the OM, the T-12, the rent roll, and the leases, extracts the numbers into your own model with every value traceable to the page it came from, then routes the result to an analyst who owns the judgment. It does not decide the deal; it removes the mechanical hours so your team spends its time on the assumptions that move the return. It pairs naturally with a pro forma generator once the inputs are clean.
Adoption has outrun results across the industry: JLL's 2025 Global Real Estate Technology Survey found 88% of real estate investors, owners, and landlords piloting AI, yet only 5% report achieving all their program goals. As Lucas Eschapasse, CEO of NextAutomation, puts it: “A useful underwriting copilot earns trust by showing its work; every extracted number traces back to the page it came from, so the analyst confirms it in seconds instead of rebuilding the model by hand.”
CAPABILITIES
What's included
Deal intake and evidence extraction with source provenance
Explicit assumptions with owner and review timestamp
Base, downside, and upside cases with subordinate model artifacts
Market, physical, legal, operational, and execution risk register
Human-owned IC recommendation, price ceiling, conditions, and memo
Ready to implement this in your firm?
NextAutomation builds this as a custom system tailored to your tools, team size, and investment strategy.