Automate Lease Abstraction and Critical Date Tracking

Small property management firms often rely on a combination of general-purpose software and spreadsheets. Platforms like AppFolio or Yardi offer calendar features, but their data models are fixed. They are not designed to track a non-standard co-tenancy clause or a unique HVAC maintenance provision that was negotiated into a specific lease. These critical, bespoke terms end up in a generic notes field, invisible to the system's reporting and alert functions.

This forces property managers back into a manual, error-prone workflow. For example, a manager with a portfolio of 80 leases must manually review dozens of PDF documents and a master Excel spreadsheet at the end of each month. They are searching for upcoming option deadlines, rent escalations, and insurance certificate expirations. A single typo in a date formula, like entering 1/7/2025 instead of 7/1/2025, can cause the firm to miss a 90-day renewal notice period. This mistake can lead directly to months of unplanned vacancy and tens of thousands in lost revenue.

The structural issue is that commercial leases are not standardized data; they are complex legal contracts. Off-the-shelf software treats lease administration as a data entry problem into a rigid schema. It cannot handle the variability and nuance of negotiated commercial real estate agreements. As a result, the most valuable information in the lease remains trapped in unstructured PDF files, and the riskiest work remains a manual, high-stakes task.

We would begin with a discovery phase focused on your documents. You would provide 5 to 10 sample leases, and we would work together to define the exact 15-20 data points that matter most to your operations, from commencement dates to specific CAM audit rights. This initial audit produces a precise data schema for the system and a clear definition of success before any code is written.

The technical architecture is designed for reliability and low operating costs. Leases are uploaded to a secure portal, which triggers an AWS Lambda function. This function uses Python with the PyMuPDF library for text extraction and the Claude 3 Sonnet API to parse the text into a structured JSON object based on the schema from discovery. This structured data is then stored in a Supabase PostgreSQL database, creating a queryable single source of truth for your entire portfolio. We choose this serverless stack because it scales to zero, meaning hosting costs are typically under $50 per month.

The delivered system includes the secure upload interface and access to the Supabase database. A second, scheduled Lambda function runs daily, querying for any critical dates within the next 90, 60, or 30 days. You receive a single, consolidated email digest with all upcoming events, eliminating the need for manual calendar checks. You receive all the source code, a technical runbook, and full ownership of the data and infrastructure.