Automate Client Calls and Scheduling with an AI Voice Agent
An AI voice agent answers calls 24/7, handling common questions about services, pricing, and availability. It qualifies leads based on your criteria and books appointments directly into your scheduling software.
Syntora designs and builds AI voice agents for construction client intake, focusing on automating common inquiries and appointment scheduling. We apply a well-understood architectural pattern using FastAPI, AWS Lambda, and Claude API to create intelligent conversational systems. Syntora's expertise delivers a reliable system configured to your specific operational needs.
The engagement scope for an AI voice agent for construction client intake depends on the complexity of your lead qualification logic and the number of existing systems needing integration. For example, a system with simple "service area and job type" qualification connecting to a standard calendar like Calendly would represent a more focused build. A system requiring checks for project manager availability in a custom CRM and querying material lead times would involve more in-depth discovery and development.
What Problem Does This Solve?
Standard business phone systems use rigid IVR menus ("Press 1 for sales..."). Callers hate them and often hang up. A potential client with a specific question about shingle types will not navigate a five-layer menu; they will call the next contractor on Google.
A homeowner calls about a leaky roof. They want to know if you service their town, if you offer emergency tarping, and what the initial inspection fee is. A simple chatbot builder or a basic call forwarding service cannot answer these multi-part questions. It can only route calls or collect a name and number. The lead either gets frustrated or leaves a message, and by the time you call back 2 hours later, they have already booked with a competitor who answered the phone.
Off-the-shelf voice AI solutions sound impressive but lack the specific context of your business. They cannot check your team's real-time availability in Acuity Scheduling or query your price list in a Google Sheet for "asphalt shingle repair per square foot." This forces them to give generic answers or escalate every call to a human, defeating the purpose of automation. Your business logic is unique; a generic tool cannot capture it.
How Would Syntora Approach This?
Syntora's approach for an AI voice agent begins with a discovery phase to document your most common client questions and lead qualification criteria. These would be mapped to a structured knowledge base stored in Supabase, utilizing pgvector for semantic search. This setup allows the agent to find precise answers, rather than relying solely on keyword matches. Syntora would integrate with your existing calendar API, such as Calendly or Acuity, to access real-time availability.
The core agent architecture typically involves a FastAPI application deployed on AWS Lambda. When an incoming call connects via a Twilio phone number, Lambda invokes the Python function. The audio is transcribed, and the text is then sent to the Claude 3 Sonnet API alongside your knowledge base. Claude generates a conversational response, which is converted to speech and streamed back to the caller. Syntora has built document processing pipelines using Claude API for financial documents, and similar patterns apply to voice agent interactions for construction-related inquiries.
For appointment scheduling, the agent would follow a defined workflow. It would confirm the service type, verify the caller's address against your service area using a PostGIS query in Supabase, and present available slots from your calendar. Upon confirmation, the agent would book the appointment via your scheduling tool's API and send a confirmation SMS using Twilio.
All call transcripts and agent actions would be logged to a Supabase table. Syntora would build a Vercel dashboard for reviewing conversations and agent performance. An alert mechanism, such as a Slack notification triggered by a structlog entry, could be configured for instances where the agent is unable to answer a question after multiple attempts. The delivered system would include the full codebase and documentation.
What Are the Key Benefits?
Answer Every Call, Instantly, 24/7
Never miss another lead. The agent answers on the first ring and can handle 10 simultaneous calls, something impossible for a human office manager.
Capture Leads, Not Voicemails
Instead of paying a live answering service $2 per call to take a message, the AI agent qualifies and books the lead for less than $0.30 per conversation.
Your Business Logic, Your Code
You get the full Python codebase in your GitHub repository. The knowledge base and call logs are in your own Supabase database, not a vendor's black box.
Know When a Conversation Fails
Get a Slack alert with the full transcript if the agent cannot answer a question or schedule a booking. This lets you update the knowledge base in minutes.
Books Directly Into Your Existing Calendar
The agent connects to Calendly, Acuity, or Google Calendar. Booked appointments appear instantly with all client details, no manual data entry required.
What Does the Process Look Like?
Discovery and Knowledge Base Setup (Week 1)
You provide a list of common questions, your service area, and scheduling rules. We create the initial knowledge base and grant you access to the Supabase project.
Core Agent Development (Week 2)
We build the FastAPI application and connect it to the phone system and Claude API. You receive a private phone number for testing the agent's core conversational abilities.
Integration and Deployment (Week 3)
We connect the agent to your live scheduling software and deploy it on AWS Lambda. You receive a Vercel dashboard to monitor call logs and agent performance.
Live Traffic and Tuning (Weeks 4-6)
The agent goes live on your main business line. We monitor calls for 2 weeks, tune the knowledge base, and then hand over the system with a full runbook.
Frequently Asked Questions
- What factors determine the project cost and timeline?
- Cost depends on the number of unique services it needs to understand, the complexity of your qualification logic, and the number of external systems it must connect to. A basic Q&A and scheduling agent for one service takes about 3 weeks. An agent that queries multiple internal systems to create custom quotes can take 5-6 weeks.
- What happens if the AI misunderstands a caller or cannot help them?
- The agent is programmed to escalate gracefully. After two failed attempts to understand a request, it says, "I'm having trouble understanding. Let me connect you with our office manager." It then automatically transfers the call to a human number you specify. This ensures a frustrated caller can always reach a person without hanging up.
- How is this different from a service like GoHighLevel's AI receptionist?
- GoHighLevel offers a generic AI that books appointments into its own platform. It cannot deeply integrate with your specific business rules or external tools like a custom CRM. Syntora builds a custom agent that uses your exact qualification logic and connects to the tools you already use. You also own the code and data, unlike with a bundled SaaS feature.
- Can the voice agent understand different accents and noisy environments?
- Yes. We use speech-to-text models trained on diverse audio. For contractors, we specifically test it with background noise like saws or traffic. While extreme noise can be a challenge for any system, it reliably transcribes calls from loud job sites or cars, a common failure point for simpler systems.
- How do I update the agent's knowledge if my services or prices change?
- You get access to the Supabase database where the knowledge base is stored. It is a simple table where each row is a question-answer pair. To update a price or add a new service, you just edit the text in the table. The changes are live instantly on the next call. No code changes are required for routine updates.
- Are the call recordings and client information kept private?
- Absolutely. The entire system is deployed in your own AWS and Supabase accounts. Syntora does not store any of your data after the project handoff. We use APIs from providers like Anthropic and Twilio that have strict data privacy policies and do not train their models on your API data. You have full control over all call transcripts.
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