Build a Property Management Voice AI You Actually Own
Choose a partner who delivers the full source code and avoids per-seat licensing fees. They should have direct experience integrating CRMs with large language models.
The complexity of a voice AI build depends on your current systems. Integrating with a modern property management system (PMS) with a documented API is a standard project. Connecting to older, on-premise systems or requiring real-time data syncs with multiple platforms increases the scope.
We built a voice system for a property management company with 15 leasing agents handling 500 inbound calls a week. The system went live in 4 weeks, answered 70% of common questions without human intervention, and reduced unqualified tour bookings by 60%.
What Problem Does This Solve?
Property management teams often try off-the-shelf voice AI platforms first. Services like VAPI.ai or Bland.ai offer impressive demos but are black boxes. Customizing their logic to query your PMS for a specific unit's 'market ready' date is often impossible. Their per-minute pricing also becomes costly at scale; 500 three-minute calls a week can exceed $900 per month in usage fees alone.
Another common approach is using a tool like Twilio Studio. It's designed for building IVR call flows, but its native speech recognition is not conversational. To handle complex questions, you have to connect it to an external function. Using a no-code connector adds 2-4 seconds of latency, which is an eternity on a phone call. The caller hears dead air and hangs up, thinking the line is broken.
A 20-person firm tried this. Their Twilio Studio flow was meant to ask if a caller was a prospect or resident. It misclassified 30% of calls, routing frustrated residents to the leasing queue. They couldn't add a custom integration to their PMS, AppFolio, so the bot couldn't answer the single most common question: "Do you have any two-bedrooms available next month?"
How Does It Work?
We start by connecting directly to your telephony provider, like Twilio or Telnyx, via a webhook. As a call comes in, we stream the audio to a real-time transcription service. We use Deepgram for this, as it returns text with a latency of under 250ms. The raw audio and transcript are stored in a Supabase database that you own for logging and future analysis.
The core logic is a Python application built with FastAPI and deployed on AWS Lambda. This serverless architecture handles unpredictable call volume without you managing servers. The FastAPI endpoint receives the live transcript from Deepgram and sends it to the Claude 3 Haiku API for intent recognition. Claude’s 500ms response time is critical for maintaining a conversational pace.
Once Claude identifies an intent, like a leasing inquiry for a specific unit type, the FastAPI service executes the business logic. It makes a direct, authenticated API call to your PMS using the httpx library for asynchronous requests. We parse the availability data, pass it back to Claude to generate a natural language response, and then use a text-to-speech API to play the answer. The entire turn, from spoken question to spoken answer, takes less than 1.5 seconds.
For monitoring, we use structlog to write structured JSON logs to AWS CloudWatch. This allows us to create specific alerts. If the PMS API latency spikes above 2 seconds or Claude's API returns errors on more than 5% of calls, we get an immediate notification. The entire system's cloud hosting costs are typically under $50 per month for a volume of 10,000 calls.
What Are the Key Benefits?
Live in 4 Weeks, Not 6 Months
We complete the build from telephony integration to PMS connection in under 20 business days. Your system starts answering calls immediately, not after a quarter-long enterprise rollout.
Pay for Usage, Not Per-Agent Seats
A single fixed-price build with low, direct cloud hosting costs after launch. You pay for the raw API calls you use, not a recurring SaaS subscription that scales with headcount.
Your Code, Your Cloud, Your Data
We deliver the full Python source code to your GitHub repository. The entire system runs in your AWS account, and all call data is stored in your database.
Alerts When It Breaks, Not After a Renter Complains
We configure CloudWatch alerts for latency spikes and API error rates. You know about issues in real-time, before they impact your leasing operations.
Connects Directly to Your Property Management System
Native API integration with your PMS, whether it is AppFolio, Yardi, or another platform. The AI provides real-time unit availability, not static, pre-programmed answers.
What Does the Process Look Like?
Week 1: Scoping & Access
You provide API credentials for your PMS and telephony provider. We map your critical call flows and define the top 5-10 questions the AI must answer. You receive a technical specification document.
Week 2: Core Logic & Integration
We build the FastAPI service and connect it to your PMS API. You receive a private link to a demo interface where you can type questions and see the live data returned from your system.
Week 3: Telephony & Deployment
We connect the application logic to a new phone number for end-to-end testing. You receive the test number to call and have a real conversation with the AI.
Week 4: Launch & Monitoring
We port or forward your main leasing line to the new system. We actively monitor call logs for 30 days to tune performance and hand over a runbook covering common issues and system maintenance.
Frequently Asked Questions
- What factors influence the project cost and timeline?
- The primary factors are the number of distinct systems we need to integrate (just a PMS versus a PMS plus a separate CRM) and the complexity of your call routing logic. A straightforward leasing qualifier takes 2-3 weeks to build. A more complex system that also handles maintenance requests and resident billing questions can take 4-5 weeks. Schedule a discovery call for a fixed-price quote.
- What happens if the AI gives a wrong answer or misunderstands someone?
- The system is designed to fail gracefully. If the AI's confidence score for an intent is below a set threshold, or if a required API call fails, it doesn't guess. Instead, it says, 'I'm having trouble with that request. Let me connect you to a member of our leasing team.' This prevents bad information from being shared and logs the failure for review.
- How is this different from using an out-of-the-box agent from VAPI.ai?
- VAPI provides a managed agent but offers limited control over the core logic and no access to the source code. Our approach delivers a purpose-built system you own completely. You have full control over the AI prompts, the PMS integration logic, and the data. You also pay for raw cloud and API usage, avoiding marked-up per-minute fees that penalize high call volume.
- Will the voice AI sound robotic and unnatural?
- No. We use modern text-to-speech (TTS) APIs from providers like ElevenLabs, which offer very natural-sounding voices. The latency for TTS generation is low enough (under 300ms) that the conversation feels fluid and responsive. We select a voice that matches your brand, and can even clone a specific voice, though this adds to the project timeline.
- Where is our customer call data stored?
- All data, including audio files and transcripts, is stored directly within your own cloud infrastructure, not ours. Typically, this means an AWS S3 bucket and a Supabase database that you control. Syntora does not retain any of your operational data after the initial 30-day monitoring and support period, unless you choose a monthly maintenance plan.
- Can we use our existing main leasing phone number?
- Yes. In most cases, we can port your existing number from your current carrier to a programmable provider like Twilio. The porting process is managed to ensure there is no service interruption. If you prefer not to port the number, we can configure call forwarding from your current provider to the new AI system. To the caller, the experience is seamless.
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