Automate AMI Sorting and Waitlist Management for Lease-Up
Automate waitlist management by parsing income documents and calculating projected annual income. This data automatically sorts applicants into the correct AMI bucket for your property. Syntora offers custom engineering engagements to address the challenges of high-volume affordable housing lease-ups, where manual income calculation creates significant delays. We would design and build a system tailored to your property's specific needs, integrating with platforms like RealPage or AppFolio to ingest new applications. Our solutions implement LIHTC, HOME, and HUD compliance rules for income anticipation, focusing on the next 12 months, not trailing history. The scope of a project like this depends on factors such as your required integrations, the variety and volume of income documents, and the complexity of your compliance rules.
Syntora offers custom engineering engagements to automate affordable housing waitlist management. By building tailored systems that integrate with existing platforms and leverage AI for income document parsing, Syntora helps properties streamline applicant processing while adhering to complex LIHTC, HOME, and HUD compliance rules. These solutions provide technical buyers with robust, scalable architectures for high-volume lease-ups.
What Problem Does This Solve?
Standard property management software like RealPage and AppFolio have application portals, but their income calculation features are not built for affordable housing compliance. Their calculators often use trailing 12-month data, not the required anticipated 12-month income for LIHTC programs. They cannot reliably parse variable income from tips or gig work, forcing leasing agents into a manual review process for nearly every applicant.
This forces teams to use spreadsheets as a workaround. For a 450-unit lease-up in Austin that receives 1,500 applications in the first week, an agent must download pay stubs from AppFolio, project annual income for each applicant, check student status, verify assets for HOME units, and manually place them into an AMI tier on a master spreadsheet. At 15-20 minutes per application, this creates a 375-hour backlog before the waitlist is even sorted.
A single typo in a spreadsheet formula can misclassify an applicant, creating compliance risk or causing the team to waste days processing a file for someone who will ultimately be denied. The entire process is slow, error-prone, and does not scale during the critical first weeks of a lease-up.
How Would Syntora Approach This?
Syntora's engagement would start with a detailed discovery phase to define your specific workflow, integrate with existing systems like RealPage or AppFolio, and meticulously document all applicable LIHTC, HOME, or HUD compliance rules. This ensures the system aligns precisely with your operational and regulatory requirements.
The technical solution would involve building a custom integration layer to ingest new applicant data and documents in real time using your existing system's APIs. For document processing, we leverage large language models such as the Claude API. We have extensive experience using Claude API to parse complex documents (e.g., financial statements) and can apply this expertise to efficiently extract key income figures—like hourly wage, pay periods, tips, and bonuses—from applicant documents, returning structured JSON data.
A custom Python service, built using FastAPI, would house the core income calculation logic. This service would apply your specific LIHTC, HOME, or HUD rules to the extracted data, accurately projecting anticipated annual income. The calculated income would then be compared against your property's AMI table, securely stored in a database like Supabase Postgres.
This FastAPI service would be architected for event-driven processing and deployed on AWS Lambda. This approach offers robust scalability for high-volume lease-up periods and helps optimize hosting costs. Upon new application submission, a webhook would trigger the Lambda function, which would perform the calculation and then use the RealPage API to write the AMI tier and pre-qualification status back to the applicant's record. This allows your leasing team to access sorted lists directly within their native software.
For transparency and auditability, we integrate structured logging using tools like `structlog`, providing a complete trail of every calculation. The system would be designed to flag applicants for manual review if documents are ambiguous or parsing is uncertain, sending notifications to a designated channel with direct links to the record, thereby focusing manual efforts where they are most needed.
A typical engineering engagement for this type of system ranges from 12 to 20 weeks, varying with integration complexity and rule variations. Key client contributions include providing API access to existing systems, detailed AMI tables, and comprehensive documentation of compliance rules. Deliverables would encompass the fully deployed custom system, complete technical documentation, and a thorough handover for your operational team.
What Are the Key Benefits?
Go from 40-Hour Bottleneck to 15-Second Processing
Eliminate manual data entry. The system ingests, parses, calculates, and sorts an applicant file in under 15 seconds, turning a week-long task into a real-time process.
Fixed Build Cost, Not a Per-Application Fee
We scope a one-time build cost. After launch, you only pay for cloud usage, typically under $50 per month for thousands of applications, avoiding expensive per-unit SaaS fees.
You Get the Full Source Code and IP
At handoff, you receive the complete Python codebase in your private GitHub repository. You own the intellectual property and can have any internal or external developer modify it.
Audit-Ready Logs for Every Calculation
Every automated decision is logged with `structlog` and sent to a dashboard. This creates a transparent, auditable record for each applicant, crucial for LIHTC and HOME compliance reviews.
Works Inside RealPage and AppFolio
The system integrates directly with your existing property management software. Your leasing team works from a familiar interface, now with automated AMI sorting and pre-qualification data.
What Does the Process Look Like?
Week 1: Scoping and API Access
You provide read-only API credentials for RealPage or AppFolio and a sample of 20-30 application files. We map your exact AMI tables and income verification rules. You receive a detailed project specification.
Weeks 2-3: Core System Development
We build the document parsing, income calculation engine, and API integrations. You receive access to a staging environment to test the system with sample applications.
Week 4: Deployment and Live Testing
We deploy the system on AWS Lambda and connect it to your live environment. The system processes the first 100 live applications in a monitored state. You receive the production dashboard credentials.
Weeks 5-8: Monitoring and Handoff
We monitor system performance and accuracy for 30 days post-launch. After this period, we deliver the full source code, API documentation, and a runbook for maintenance and troubleshooting.
Frequently Asked Questions
- What does a system like this cost to build?
- Pricing depends on the number of unique income verification rules and the complexity of your property management software integration. A standard build for a single property type with RealPage integration is a fixed project fee. We provide a firm quote after a 45-minute discovery call where we review your specific needs and application volume.
- What happens if an applicant's documents are unreadable?
- The Claude API is highly accurate, but it can fail on blurry photos or handwritten notes. If the document parser's confidence score is below 95%, the system automatically flags the application for manual review. Your leasing agent receives a Slack notification with a direct link to the applicant's file in AppFolio or RealPage.
- How is this different from RealPage AI Screening?
- RealPage AI Screening focuses on credit and background checks, not the nuanced income anticipation required for LIHTC compliance. It is not designed to calculate projected 12-month income from variable sources or sort applicants into specific AMI tiers. Our system is built exclusively for that purpose, augmenting RealPage's platform rather than replacing it.
- What kind of ongoing maintenance is required?
- The system is designed to run with minimal intervention. The primary maintenance task is updating the AMI tables annually, which is a simple data update in the Supabase database. We provide a runbook that shows how to do this. We also offer an optional monthly support plan for ongoing monitoring and updates.
- We have multiple properties with different AMI levels. Can it handle that?
- Yes. The system stores AMI tables on a per-property basis. When an application comes in for a specific property, the calculation engine pulls the correct AMI limits for that location. This ensures a 30% AMI applicant for Property A is not compared against the 50% AMI limits for Property B.
- Can you connect to Yardi or Entrata?
- We focus on RealPage and AppFolio because their APIs are mature and well-documented. If you use another system like Yardi or Entrata, we can investigate their API capabilities. A custom integration may be possible but would require an initial technical discovery phase to assess feasibility and define the scope.
Related Solutions
Ready to Automate Your Property Management Operations?
Book a call to discuss how we can implement ai automation for your property management business.
Book a Call