Automate Maintenance Request Triage for Apartment Buildings

Most property management companies rely on the built-in ticketing of their PMS, like AppFolio or Buildium. These systems use basic keyword filtering. If a tenant includes the word 'fire' or 'flood', the ticket is flagged. This approach fails with any request that requires interpretation. The systems are designed as databases with forms, not as language-processing engines.

Consider a 1,500-unit portfolio. A tenant submits a request at 2 AM saying, 'The toilet keeps running and I see water on the floor near the wall'. The system sees 'toilet running' and categorizes it as a low-priority plumbing issue. No human sees it until 9 AM. By then, the slow leak has saturated the subfloor and is dripping into the apartment below. A $50 wax ring replacement has become a $5,000 drywall and flooring repair because the system could not infer 'water on the floor near the wall' as a critical water intrusion risk.

This is not a feature gap; it is an architectural limitation. Platforms like Yardi and AppFolio are excellent systems of record, but their core function is accounting and lease management. Their automation capabilities are built on rigid, pre-defined rules. They cannot understand the semantic difference between 'my faucet is dripping' (low priority) and 'the ceiling is dripping' (high priority). The result is that a skilled property manager must still manually read every single request to prevent a disaster, defeating the purpose of an automated intake.

The first step would be a data audit. Syntora would analyze 6-12 months of your historical maintenance tickets to understand your specific request patterns and internal priority levels. You provide the raw data export and your current triage guidelines. The audit produces a clear map of which types of tenant-submitted language correlate with high-priority outcomes, forming the basis for the AI system's logic.

The technical approach uses a lightweight FastAPI service that listens for new maintenance requests. When a ticket arrives, its text is sent to the Claude API with a detailed prompt engineered from the data audit. Claude extracts the issue type, location, and inferred urgency, returning a structured JSON object with a priority score from 1-5 and a one-sentence summary. This entire process completes in under 3 seconds and the system is deployed on AWS Lambda to keep hosting costs below $30 per month.

The delivered system integrates directly with your current PMS. Your property managers would see a new 'AI Priority' field and a summary right on their existing dashboard. No new software to learn. The system acts as an intelligent layer on top of your existing tools, ensuring every request is accurately assessed 24/7, allowing your team to act on true emergencies instantly.