Build a Voice AI for After-Hours Property Management
A custom voice AI agent is best for small property management firms handling after-hours calls. It triages emergency requests, logs routine maintenance, and routes calls without human intervention.
We built a voice AI for a 7-person property management company with 400 residential units. They were missing 15% of after-hours emergency calls, leading to tenant complaints. The system went live in 2 weeks, automatically handling 90% of calls and logging tickets directly into their property management software.
The system's complexity depends on your triage logic and current software. A firm with a simple on-call schedule and AppFolio access is a standard build. A multi-state operator with different rules for each property and a custom-built CRM requires a more detailed integration plan.
What Problem Does This Solve?
Most property managers first try a standard phone tree or IVR from a service like RingCentral. This fails because tenants in a panic, like with a burst pipe, will not navigate a “press 1 for X” menu. They hang up and call repeatedly, or worse, the issue escalates. This system cannot distinguish a real emergency from a simple request.
Next, they might try an off-the-shelf conversational AI platform like Voiceflow connected to Twilio. This is better, but these platforms often struggle with the stateful, multi-step logic property management requires. A single call might need to check the on-call schedule in Google Sheets, verify the tenant's unit number via an AppFolio API call, and then text the correct plumber. Each step burns through tasks, driving up a variable bill that can exceed $400/month for a 300-unit building.
These tools are not built for business-critical logic. When an API call to the property management software fails, the workflow often just stops, leaving the tenant in limbo. There is no built-in logic to retry the connection or escalate to a human property manager, which is a critical failure mode when dealing with property emergencies at 2 AM.
How Does It Work?
We start by mapping your exact after-hours protocol into a state machine. We define what constitutes a P1 emergency (fire, flood) versus a P2 urgent request (no heat) or a P3 routine ticket (dripping faucet). This logic becomes the core instruction set for the Claude API, which guides the conversation.
We provision a phone number via Twilio and connect it to a FastAPI application running on AWS Lambda. When a call comes in, Twilio transcribes the user's speech in real time and sends it to our API. The FastAPI service sends the text to the Claude API, gets back structured JSON classifying the issue, and decides the next step. The entire conversational turn, from tenant speaking to AI responding, completes in under 700ms.
If Claude identifies an emergency, the FastAPI application uses httpx to perform an immediate lookup. It can query a Supabase database or a simple Google Sheet to find the on-call technician for that specific property and time. It then sends a high-priority SMS alert via the Twilio API with the unit number, tenant name, and issue summary. The system can process over 100 calls per hour during an outage.
For non-emergency requests, the system gathers the necessary details and makes a direct API call to your property management software, such as AppFolio or Buildium, creating a maintenance ticket. Every call transcript, AI classification, and action taken is written to a log stream using structlog, providing a full audit trail for every after-hours incident.
What Are the Key Benefits?
Launch in 10 Business Days
Go from initial call to a live, production-ready voice AI in two weeks. Stop missing emergency maintenance calls this month, not next quarter.
Pay for Usage, Not Per Agent
Your cost is based on AWS Lambda and Twilio usage, typically under $50/month. Avoid fixed monthly fees from call centers or per-seat SaaS tools.
You Own the Code and Logic
We deliver the complete Python source code to your company's GitHub repository. You are not locked into our service or any proprietary platform.
Know About Failures Before Tenants Do
The system sends an immediate alert via AWS CloudWatch if API error rates exceed 2% or latency spikes, ensuring we can fix issues proactively.
Logs Tickets Directly in Your PMS
The voice AI integrates with AppFolio, Buildium, and other platforms via their APIs. Your team manages all tickets in the system they already use.
What Does the Process Look Like?
Protocol Mapping (Week 1)
You provide your after-hours call handling procedures and API credentials for your PMS. We deliver a decision-flow diagram for your approval.
Core System Build (Week 1)
We build the FastAPI application and configure the Claude API with your triage logic. You receive a dedicated phone number to test the AI.
Integration and Deployment (Week 2)
We connect the voice AI to your PMS and on-call schedule, then deploy to AWS Lambda. You receive deployment confirmation and access to live logs.
Monitoring and Handoff (Weeks 3-4)
We monitor real call traffic for two weeks and fine-tune the AI prompts. You receive the full source code, a runbook, and system documentation.
Frequently Asked Questions
- How much does a custom voice AI cost to build?
- The final price depends on the number of unique triage paths, the specific property management software we need to integrate with, and any custom logic like multi-language support. A typical build takes 2-4 weeks. After a 30-minute discovery call where we review your process, we provide a fixed-price proposal. There are no hourly charges or hidden fees.
- What happens if the AI cannot understand a tenant?
- The system is designed to fail gracefully. If the AI cannot confidently classify the issue after two attempts, it automatically says, “I’m having trouble understanding. I am connecting you to our on-call manager now.” It then forwards the call to a pre-designated human emergency line. The entire failed transcript is flagged for our review to improve the core prompts.
- How is this different from a virtual receptionist like Smith.ai?
- Virtual receptionists are human-powered services that bill per call or per minute. They are great for complex, unpredictable conversations. Syntora builds an automated system that you own. It is designed to handle the 90% of calls that follow a predictable script (log ticket, escalate emergency) for a fraction of the per-call cost of a human agent.
- Can the AI handle Spanish-speaking tenants?
- Yes. We can configure the system to detect the caller's language and respond in kind, using a Spanish-language model for both transcription and generation. This is a common requirement and is scoped during our initial discovery call. The underlying APIs from Twilio and Anthropic have strong multi-language support, so this does not significantly increase technical complexity.
- Does the AI voice sound robotic?
- No. We use modern text-to-speech engines that produce natural-sounding voices. We can select from a variety of voices and dialects to match your brand. The goal is a professional, calm, and clear interaction that reassures tenants during a potentially stressful situation, not a jarring, robotic-sounding system.
- What happens after the system is built and handed off?
- You own the code and can have any Python developer manage it. We also offer an optional flat-rate monthly maintenance plan. This covers hosting costs, prompt tuning based on call logs, dependency updates, and on-call support for any system outages. Most clients choose this for the first year to ensure the system remains stable as their business grows.
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