Automate Tenant Onboarding with a Custom AI Workflow

Most property management companies rely on the built-in features of their Property Management Software (PMS) like AppFolio or Buildium. These tools offer basic application forms but their screening workflows are rigid. They cannot intelligently parse uploaded documents, forcing leasing agents to manually open PDFs, find the net income on a pay stub, and type it back into a form. This workflow breaks entirely when an applicant is a freelancer with bank statements instead of pay stubs, pushing the process offline into spreadsheets and email.

To compensate, teams use separate screening services like TransUnion SmartMove or RentPrep. This creates a painful, multi-step process. A leasing agent downloads an application from the PMS, logs into the screening portal, re-types the applicant's name, SSN, and date of birth, runs the check, then interprets a PDF report. The agent then manually updates the status back in the PMS. This 20-minute cycle, repeated 15 times a day during peak season, consumes over 5 hours of an agent's time and is prone to costly data entry errors.

The structural problem is that these tools are not built for integrated workflow automation. The PMS is a system of record, and the screening tool is a point solution for a single task. There is no central intelligence to receive an application, extract information from unstructured documents like IDs and bank statements, execute a set of business rules, call third-party APIs for background checks, and write the final, auditable decision back to the source system. This architectural gap forces teams into time-consuming and error-prone manual work.

The first step is a discovery audit of your current tenant screening process. Syntora maps every action from the moment an application is received to when a lease is sent. We review your document types (IDs, pay stubs, 1099s), your screening criteria, and the API capabilities of your existing PMS and background check providers. The outcome is a detailed process diagram and technical plan you approve before any code is written.

The technical approach uses a central FastAPI service written in Python to orchestrate the entire workflow. For document processing, the system would use the Claude API to extract and structure data from applicant documents. We have used this pattern to process complex financial reports, and the same technique applies to reading income figures from pay stubs or identifying large deposits in bank statements. This service connects to screening provider APIs to run checks and applies your specific business logic (e.g., income must be 3x rent, credit score over 650) to reach a decision.

The delivered system runs on AWS Lambda, so you only pay when an application is being processed. It integrates directly with your existing PMS. Your leasing agents do not have to learn a new tool; they simply see the applicant's status update automatically to “Approved” or “Rejected,” with a link to a detailed report showing all the data and the reason for the decision. You receive the full source code, a runbook for maintenance, and the system is deployed in your own AWS account.