Capture Every After-Hours Lead with AI Automation
Most small businesses miss over 80% of calls that come in after 5 PM and on weekends. An AI phone agent can capture these leads by answering 24/7 and scheduling follow-ups into your calendar.
The system's complexity depends on the required tasks. An agent that only books appointments and answers basic FAQs is a straightforward two-week build. An agent that needs to qualify leads against a multi-step script and integrate with a custom CRM requires more discovery and integration time.
We built an after-hours agent for a 12-person HVAC company. They were receiving 20-30 calls per night that went to a generic voicemail. The new AI agent now answers every call, qualifies the urgency, and books 4-5 new, confirmed service appointments each night directly into their scheduling software.
What Problem Does This Solve?
Most businesses route after-hours calls to a standard voicemail box. This fails because 85% of potential customers who reach a voicemail will not leave a message; they simply hang up and call the next business on the list. You are not just missing a call, you are sending leads directly to your competitors.
Live answering services seem like a better option, but they introduce new problems. These services charge $2 to $3 per minute and rely on human agents following rigid scripts. They cannot answer company-specific questions, qualify leads with any real depth, or integrate with your business systems beyond creating a basic contact record. A client of ours, a law firm with 8 attorneys, was paying $1,200/month for a service that could not distinguish a high-value personal injury case from a simple traffic ticket inquiry.
Basic interactive voice response (IVR) systems that use 'press 1 for sales' menus only add friction. Callers expect to speak in natural language, not navigate a phone tree. When a customer says 'My basement is flooding,' a rigid IVR cannot understand the urgency and route the call correctly. This poor experience frustrates callers and makes your business seem outdated.
How Does It Work?
We begin by analyzing your last 3 months of call logs to identify the top 5-7 reasons people call after business hours. This informs the conversational paths the AI agent will follow. We provision a new phone number through Twilio and set your main business line to forward all calls to it outside of your 9-to-5 schedule.
The core of the system is a Python application built with the FastAPI framework and deployed on AWS Lambda. When a call arrives, Twilio provides a real-time speech-to-text transcription. This text is sent to a FastAPI endpoint, which passes it to the Claude 3 Sonnet API. The API uses a system prompt we design to define the agent's persona, goals, and the 3-4 key questions it must ask to qualify a lead.
Once a lead is qualified, the agent uses the `httpx` library to make an asynchronous API call to your CRM, creating a new contact and deal record. For a regional insurance agency, we built an integration that populates their claims management system with initial loss details. The entire interaction, from the first ring to a new record in their system, completes in under 90 seconds. All call transcripts and outcomes are logged to a Supabase database for review.
This architecture handles over 500 calls per month for under $30 in monthly hosting costs on AWS. We implement structured logging using `structlog` and configure CloudWatch alarms. If any API call to your CRM returns a non-200 status code, we receive a Slack notification within 60 seconds, allowing us to investigate the failed integration before it impacts your business.
What Are the Key Benefits?
Launch in 2 Weeks, Not 2 Quarters
Your AI agent is live and answering calls in 10 business days. We skip the lengthy sales cycles of enterprise call center software.
Pay Per Call, Not Per Agent
Infrastructure costs scale with usage, typically under $50/month. Avoid the fixed $1,500+ monthly cost of a human answering service.
You Receive the Full Source Code
The complete Python codebase is delivered to your GitHub account. No vendor lock-in, no black boxes, and no per-seat fees.
Alerts on Failed Integrations in 60 Seconds
CloudWatch alarms monitor the system 24/7. If a CRM entry fails, we get a Slack alert instantly, not when a lead complains.
Connects Directly to Your CRM
Leads and call summaries are pushed into HubSpot, Salesforce, or your industry-specific platform via custom API integration. No more manual data entry.
What Does the Process Look Like?
Call Analysis (Week 1)
You provide access to call logs or describe common call types. We deliver a conversation flow diagram outlining the AI's script and decision points.
System Build (Week 1)
We write the Python code, configure the Twilio phone number, and connect to the Claude API. You receive a demo number to test the agent yourself.
Integration & Deployment (Week 2)
We connect the agent to your CRM and deploy the system on AWS Lambda. You receive API credentials and a test confirmation that leads are creating correctly.
Monitoring & Handoff (Weeks 3-4)
We monitor live call traffic for 2 weeks to tune the agent's responses. You receive a runbook with full documentation and the final source code.
Frequently Asked Questions
- How is the project price determined?
- Pricing is fixed based on complexity. A simple appointment-booking agent is a standard 2-week build. An agent that needs to look up customer data in an ERP and answer questions about order status requires more integration work and takes closer to 4 weeks. We provide a fixed-price quote after our initial discovery call at cal.com/syntora/discover.
- What happens if the AI misunderstands a caller?
- The agent is programmed with fallback logic. If it fails to understand a request after two attempts, it says, 'I'm having trouble understanding. I'll connect you to our general voicemail where you can leave a detailed message.' The full call transcript is logged and flagged for our review so we can improve the agent's script.
- How is this different from a service like Smith.ai?
- Smith.ai uses human receptionists, which is why they charge per-call or a high monthly fee. We build a software asset that you own. Our AI agent is faster, cheaper to run at scale, and can be customized to perform tasks a human cannot, like querying your internal database in real-time to answer a specific customer question.
- Does the AI sound like a robot?
- No. We use high-quality text-to-speech models from Amazon Polly that are nearly indistinguishable from human speech. We can choose from a library of natural-sounding voices with different accents and tones. The speaking style is configured to match your brand, from formal and professional to friendly and casual.
- Can the agent handle more than just phone calls?
- Yes. The core logic is an API. While the initial build is for voice calls via Twilio, the same FastAPI endpoint can be connected to an SMS chatbot or a website chat widget. This allows you to provide a consistent automated experience across multiple channels without rebuilding the entire system from scratch.
- How is caller information and privacy handled?
- We are not a SaaS platform; we do not store your customer data. The system is deployed on your own cloud infrastructure. Call data passes through the Claude API, which has a zero-retention policy. All transcripts and personally identifiable information are logged directly to your own secure Supabase database, which you fully control.
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