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Case Study · AI Workflows · Protech

Turning Complex Lease Documents Into Structured, Actionable Data

Lease Attendant needed a better way to onboard and manage commercial lease information without relying on time-consuming manual data entry and disconnected workflows.

The Challenge

Commercial leases are difficult to standardize and even harder to manage manually

Every new lease required landlords to manually review dense legal documents and enter critical information into the system. Commercial leases vary dramatically in structure and complexity, making traditional OCR and rules-based parsing unreliable and difficult to scale.

The platform also needed a better way to proactively manage lease obligations, reminders, and tenant communications.

  • Lease terms, rent schedules, and escalation clauses varied significantly between properties
  • Manual data entry created administrative overhead and increased the risk of errors
  • Traditional OCR and template-based parsing could not reliably handle inconsistent lease formats
  • Ongoing obligations like reconciliations, maintenance schedules, and rent reminders were difficult to track manually
  • The system needed a way to automate communications while remaining context-aware and accurate

What We Did

An AI-powered workflow that transforms uploaded leases into structured system data

  • Built an upload-based workflow for processing commercial lease PDFs
  • Used Google Gemini to extract key information from unstructured legal documents
  • Automatically populated lease records with dates, schedules, obligations, and property details
  • Engineered a flexible schema capable of supporting highly variable lease structures
  • Built AI-assisted messaging workflows for landlords and tenants
  • Generated automated reminders for rent deadlines, reconciliations, and maintenance requirements
  • Designed workflows to reduce manual onboarding and ongoing administrative effort
  • Created a scalable architecture capable of supporting large property portfolios
An upload and done workflow, where landlords upload their lease PDF documents and our AI process extracts all of the vital information
We engineered a flexible, table-base schema for the rent schedule

The Result

A lease management system that acts more like an assistant than a database

Landlords no longer need to manually enter large amounts of lease data

Complex lease structures can be processed and organized automatically

Ongoing lease obligations are easier to track and manage

Automated messaging workflows improve responsiveness and organization

The platform is more scalable and efficient for managing growing portfolios

AI-assisted workflows for lease tracking, reminders, and tenant communication

Key Takeaway

AI is most effective when applied to operational bottlenecks that are difficult to automate using traditional systems.

This project transformed lease onboarding and management from a manual administrative process into a scalable, AI-assisted workflow.

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