Automate Your Tenant Screening Workflow with AI

Most small property management companies rely on the screening features built into their Property Management System (PMS) like AppFolio or Buildium. These tools offer a basic pass/fail recommendation but operate as a black box. You cannot customize the scoring logic to match your specific portfolio's risk tolerance or properly analyze non-standard income documents, like a freelance applicant's bank statements.

This forces teams into manual, time-consuming workarounds. Consider a 3-person firm managing 150 units that receives 10 applications for one property. They use a standalone service like TransUnion SmartMove, requiring them to manually input applicant data for each of the 10 reports. An employee then downloads 10 separate PDF files, reads through each one, and manually checks them against a list of criteria like income above 3x rent and no evictions in the last 7 years. This information is then copied into a spreadsheet for comparison. The process for one vacant unit consumes half a day of skilled staff time.

Standalone screening portals also introduce significant data entry risk. A single typo in a social security number can return an incorrect report, leading to a wrongful rejection or a high-risk approval. The core issue is that these off-the-shelf tools are designed for one-off checks, not for integrated workflow automation. Their architecture is not built to ingest and parse varied document types or apply custom, multi-faceted business rules. They solve a data retrieval problem, not a decision-making one.

The first step is a workflow audit. Syntora would meet with your team to map out your exact screening criteria, from income-to-rent ratios to specific credit score thresholds and eviction look-back periods. We would identify every document you collect and every decision point in the process. You receive a detailed scope document that outlines the complete automation logic before any code is written.

The technical approach would center on a FastAPI service acting as the workflow engine. When an application is submitted in your PMS, a webhook triggers the service. The Claude API would parse submitted documents like pay stubs and bank statements to verify income. We have used this pattern to process complex financial documents, and the same principles apply directly to tenant income verification. The service then calls external APIs for credit reports and public records, consolidating all data.

The delivered system runs on AWS Lambda, keeping hosting costs under $20 per month for a typical workload. The final output, a concise risk score and data summary, is written back into a custom field in your PMS. Your team never leaves their primary software. You receive the full Python source code, a detailed runbook, and complete control over the system, with no ongoing licensing fees to Syntora.