[2026 Latest] Automated Triage of Maintenance Requests Using NLP: Optimizing Urgency Determination Based on MECE

In rental management, maintenance requests from tenants are unpredictable and diverse. In particular, responding to emergencies such as "water leaks" or "lost keys" occurring at night or on holidays has been a factor increasing the mental and physical burden on management staff. This article explains the forefront of "automated triage," which utilizes Natural Language Processing (NLP) to analyze free-text input from tenants and automatically determine urgency. We propose a specific scheme for optimizing initial decision-making by implementing MECE (Mutually Exclusive, Collectively Exhaustive) logic into AI.

1. Implementing NLP in Rental Management: Turning Free-Text Input into Structured Data

Traditional chatbots and inquiry forms have mainly used selection (pull-down) formats. However, tenants in a state of panic have a psychological need to explain details in text. This is where Natural Language Processing (NLP) becomes crucial.

By using NLP, it becomes possible to extract structured data such as "Location: Kitchen," "Event: Water Leak," and "Severity: High" from unstructured sentences like "Water is gushing out from under the kitchen sink, and the floor is flooded." This allows management companies to grasp the situation at a glance and dramatically improves the speed of dispatching contractors.

2. Building Urgency Determination Logic Based on MECE

To prevent AI from making judgment errors, the underlying classification logic must be MECE (Mutually Exclusive, Collectively Exhaustive). It is recommended to organize urgency in rental maintenance along the following three axes.

• Safety: Electrical leakage, fire risks, building damage, etc.
• Infrastructure: Water outages, clogged toilets, lost keys, etc.
• Amenity: Unusual noises from air conditioners, peeling wallpaper, burnt-out light bulbs in common areas, etc.

Based on these axes, the AI scores each request. For example, even for the same "water leak," the NLP determines from the context whether it is manageable with a bucket or if there is a concern about damage to the floor below, and performs triage (prioritization).