Overview 

A national property management company responsible for tens of thousands of residential and commercial units struggled with operational inefficiencies driven by document overload and manual review tasks. Property teams routinely spent hours processing incoming work orders, interpreting lease documents, and reconciling arrears data across multiple systems. These manual bottlenecks diverted teams from tenant engagement and property performance optimization, delayed response times, and limited overall operational scale.

By deploying AI agents built on StackAI, the company automated core documentation and workflow processes, freeing property teams to focus on decision-making instead of document wrangling, and realized measurable operational improvements:

• Work order response times improved by up to 50%, reducing tenant complaints and accelerating repairs.

• Lease review time dropped by more than 70%, enabling analysts to focus on portfolio strategy rather than extraction tasks.

• Arrears reporting became real-time, with analysts able to act on trends days sooner than before.

• Operational consistency improved across regions, regardless of document formats or vendor systems.

Taken together, these agentic workflows reduced administrative burden, increased analytical bandwidth, and transformed how the company served tenants and owners alike.

The Problem: Slow, Manual Work Order Processing

When tenants submitted maintenance requests through multiple channels — email, portal, phone, or text — the property team’s first task was always translation. Work orders needed to be interpreted, prioritized, categorized, and routed to the appropriate vendor or technician. This was a manual, time-consuming task that required staff to interpret unstructured text, enter details into work order systems, and manually update status, then find suitable vendors and manage all next steps from there. During peak periods, this resulted in delayed responses, backlogs in critical repairs, and inconsistent communications with tenants.

The Solution: Intelligent Work Order Intake and Routing

Using StackAI, the property management company deployed a Work Order Intake Agent that automatically ingests incoming maintenance requests from all channels, interprets the intent and urgency of each request, and populates the work order management system with structured data. The agent classifies requests (e.g., plumbing vs. electrical), recommends priority levels based on built-in rules, and routes them to the correct vendor or internal technician. Staff spend less time on data entry and more on oversight and follow-up, accelerating response times and reducing tenant frustration.