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17 / Real Estate & Construction

AI-Native Lease Management

We trained an AI model to read a retail lease the way a property manager would, pulling 60+ details out of scanned PDFs and then watching every rent date, obligation and risk across the whole portfolio.

Client
GroSpace Global Pvt Ltd
Stack & approach
Real Estate AIDocument ExtractionObligation EnginePortfolio RiskPrivate Deployment
Interface screens from AI-Native Lease Management
Interface, from the 360Labs case-study deck (page 26).

The problem

Multi-brand retail operators managing 50-500+ outlets (Blue Tokai, Domino's, McDonald's) tracked leases by hand. Extracting structured data from scanned or handwritten PDFs, tracking obligations and managing payments across rent models meant manual review of every document.

Solution & architecture

AI extracts 60+ structured fields from lease PDFs, including scanned and handwritten documents. A “Confirm” and “Activate” workflow auto-creates outlets, obligations, alerts, and payment schedules. A 6-stage deal pipeline, natural-language portfolio chat, and multi-model payment generation sit on top, with per-tenant, row-level security.

Why it is built this way

  • Lease data stays tenant-scoped

    Row-level security isolates each operator

  • No manual review bottleneck

    AI reads scanned & handwritten PDFs

  • Obligations never missed

    Rules fire before a date slips

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