Automate Inbound Property Calls with a Custom AI Agent
AI voice agents answer inbound calls and collect key leasing information. They qualify prospects against your criteria and schedule showings automatically.
Syntora develops AI voice agents to automate inbound calls for property showings and lease inquiries, integrating with existing property management systems. Our engineering approach focuses on building robust conversational systems tailored to specific client needs, drawing on our experience with multi-agent platforms using FastAPI and Claude tool_use. This allows for intelligent qualification and automated scheduling, while ensuring human oversight.
The scope depends on the number of properties and required integrations. A system for 500 units connecting to AppFolio is simpler than one for 2,000 units connecting to Yardi and a separate maintenance portal. The key is mapping your existing leasing qualification questions into a structured, reliable conversation.
What Problem Does This Solve?
Most property management firms start with a standard IVR system from a provider like RingCentral. Prospects hate phone menus. When they have a specific question that does not fit an option, like “Do you allow German Shepherds?”, they press 0, defeating the automation and tying up a leasing agent.
Frustrated, teams then try an off-the-shelf voicebot. These bots can answer basic FAQs from a script but cannot check real-time unit availability in your property management software. When a prospect asks “Is unit 3B still available for a June 1st move-in?”, the bot can only say “I'll have an agent call you back,” which creates more manual work, not less.
These tools fail because they are not integrated with your core systems. A voice agent that cannot read your unit availability, check pet policies, and write a new lead record into Yardi or AppFolio is just a fancy answering machine. It cannot complete the task, so it creates a follow-up for your team, doubling the workload.
How Would Syntora Approach This?
Syntora would start an engagement by conducting a discovery phase to understand your specific property management platforms and data sources, such as AppFolio or Yardi Voyager. We would design the system to connect directly to these platforms' APIs using Python and the httpx library to access real-time unit availability, pricing, and building policies. To optimize response times and manage API usage, this data would be cached in a Supabase Postgres database.
The core conversational logic would be developed using the Claude 3 Sonnet API, carefully prompted to adhere to your organization's precise leasing qualification scripts and brand voice. Drawing on our experience building multi-agent platforms with FastAPI and Claude tool_use, we would implement a robust webhook endpoint using FastAPI. This endpoint would integrate with a telephony provider like Twilio to manage inbound call flow. The AI agent would be engineered to address complex, multi-part inquiries by querying the Supabase cache.
Scheduling functionality would be established through direct integration with your leasing team's existing calendars, using APIs such as Google Calendar or Microsoft 365. The agent would identify available time slots, confirm appointments with callers, and then create calendar events, ensuring both the prospect and the assigned leasing agent are invited. For deployment, we often consider serverless architectures like AWS Lambda, known for their scalability and cost efficiency for call handling. Our experience deploying multi-agent systems on DigitalOcean App Platform with SSE streaming also informs our deployment strategies for these types of services.
To maintain data integrity and visibility, every call transcript and its determined outcome would be logged back into your property management system, either as a new lead or as a note on an existing contact. We would implement structured JSON logging, for instance with structlog, to feed into monitoring services like AWS CloudWatch. This setup allows for continuous oversight. An alert system, perhaps to a designated Slack channel, would be configured to flag conversations for human review if the AI agent encounters difficulties beyond a defined threshold. This ensures human-in-the-loop escalation is available, a pattern we use in our own multi-agent workflow automation.
What Are the Key Benefits?
Answer 100% of Calls, 24/7
Never miss a lead again. The agent handles after-hours and weekend calls, capturing prospect details and scheduling showings when your office is closed.
Stop Paying for Empty Minutes
Unlike per-agent call center pricing, you pay for compute time. A 3-minute call costs fractions of a cent on AWS Lambda, not a fixed hourly rate.
You Own the Script and Logic
You get the full Python source code and conversational prompts. You are not locked into a vendor's rigid conversation flow; you own the qualification rules.
Real-time Alerts for Urgent Issues
Get a Slack notification if a caller mentions an emergency like a fire or flood. The system triages true maintenance emergencies from routine leasing calls.
Writes Directly to AppFolio or Yardi
No more manual data entry. Every scheduled showing and qualified lead is created automatically in your property management software, triggering existing workflows.
What Does the Process Look Like?
Week 1: System Integration & Scripting
You provide API access to your property management system and calendar. We work with you to codify your exact leasing qualification questions into a conversation script.
Weeks 2-3: AI Agent Development
We build the core voice agent using Python and FastAPI, connecting it to Twilio for telephony. You receive a private phone number for internal testing.
Week 4: Deployment & Live Testing
We deploy the system on AWS Lambda and port your main leasing phone number. You receive the full source code in a private GitHub repository.
Weeks 5-8: Monitoring & Handoff
We monitor call logs for 30 days, tuning the script for common unexpected questions. You receive a runbook detailing how to update qualification criteria and view logs.
Frequently Asked Questions
- How much does a custom AI voice agent cost?
- Pricing depends on the number of integrations (e.g., just Yardi vs. Yardi and Salesforce) and the complexity of the qualification script. A typical build is a one-time project fee. We scope the project and provide a fixed price after a discovery call. The ongoing hosting costs on AWS are usually under $50 per month.
- What happens if the AI misunderstands a caller?
- The agent is programmed to handle confusion gracefully. After two failed attempts to understand a request, it will say, 'I'm having trouble understanding. I can connect you to a leasing agent now.' It then automatically transfers the call to a human. This handoff is logged for review so we can improve the script.
- How is this different from a service like CallRail?
- CallRail provides call tracking and analytics; it tells you where calls come from. It does not answer the call or interact with the caller. Our system is an active participant in the conversation, qualifying the lead and scheduling the showing. We can use CallRail data as an input, but we replace the need for a human to answer.
- Can the agent handle different languages?
- Yes. The underlying AI models we use, like Claude 3, are multilingual. We can configure the agent to detect the caller's language and respond in Spanish, French, or others. This is scoped during the initial discovery phase, as each language requires its own tested conversation script and prompts to ensure accuracy.
- What is the voice quality like? Does it sound robotic?
- We use modern text-to-speech (TTS) engines that offer natural-sounding voices with realistic intonation and pacing. The response latency is typically under 300ms, so there are no awkward pauses. We can select from dozens of voice profiles to match your brand's tone, whether it's formal and professional or friendly and casual.
- What if our property availability changes multiple times a day?
- The system is designed for real-time data. It queries your property management system's API at the beginning of each call to get the most current list of available units. If a unit is leased while the agent is on another call, it will not be offered to the next caller. The data is always fresh.
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