Get an AI Agent to Handle Inbound Customer Service Calls 24/7
AI agents answer inbound calls using a synthesized voice, transcribing the conversation in real time. They then classify the issue, answer common questions, and create a support ticket in your CRM.
Syntora designs and engineers AI agent systems capable of handling inbound customer service calls. Our approach focuses on building scalable architectures that integrate with existing business tools like CRMs and knowledge bases. We provide the technical expertise to tailor these systems to your specific operational needs.
The system's complexity depends on the number of call types and required integrations. An agent designed only for appointment booking can typically be developed within a few weeks. An agent that must check order status in a custom ERP and access a knowledge base requires more extensive development and integration effort.
What Problem Does This Solve?
Most small businesses start with a basic Interactive Voice Response (IVR) menu or a simple voicemail-to-email service. These tools only deflect or delay customer issues, creating a bigger backlog for your team to handle the next morning. They cannot resolve problems or gather structured information from the caller.
A human answering service seems like the next logical step, but it introduces its own problems. These services often have high agent turnover and lack the specific business context to do more than take a message. A regional plumbing company with 8 technicians paid $600/month for a service that could not distinguish a burst pipe from a leaky faucet. The on-call plumber was frequently woken up for non-emergencies, defeating the purpose.
The fundamental issue is that these solutions are passive. They are message-takers that lack the real-time decision-making logic and direct system integration to act on information. They cannot check a schedule, query a knowledge base, or update a CRM record. They add a layer of human delay instead of providing intelligent automation.
How Would Syntora Approach This?
Syntora would begin by collaborating with your team to map your most common inbound call types into a logical decision tree. We would then provision a phone number through Twilio. The core application would be built in Python using the FastAPI framework. For scalability and maintenance, the entire system would typically be deployed on AWS Lambda, which automatically scales from zero to thousands of concurrent calls without server management overhead.
Upon receiving a call, the audio stream is sent to a real-time transcription service. The transcribed text is then processed by the Claude API to determine the appropriate response. The agent's spoken reply would be generated using a low-latency text-to-speech (TTS) engine, with a design goal of response times under 800ms to ensure a natural conversational flow. We have experience building document processing pipelines using Claude API for financial documents, and the same architectural patterns apply for integrating with inbound call documents and transcripts.
The agent's conversational logic would be controlled by a carefully engineered prompt. This prompt would incorporate your business rules, maintain conversation history, and leverage function-calling capabilities to interact with external systems. For instance, the system could query a Supabase vector database to retrieve answers from a knowledge base or make an API call to your internal scheduling system. Following each call, a structured JSON summary and full transcript would be written to your CRM. This typically occurs in a matter of seconds.
To ensure operational visibility and continuous improvement, Syntora would implement structured logging using tools like structlog, capturing key decisions made by the agent. This data would feed into a dashboard to monitor call volume, average call duration, and issue classification accuracy. For quality control, if the agent's confidence in classifying an issue falls below a specified threshold, the call recording and transcript could be sent to a designated Slack channel for human review.
What Are the Key Benefits?
Your 'Support Team' Never Sleeps
Handle customer calls at 3 AM on a Sunday. The agent triages urgent issues for human escalation and schedules the rest, 24/7/365.
Pay for Usage, Not for Headcount
Avoid the high recurring cost of an answering service. The AWS Lambda infrastructure typically costs under $50 per month, based on call volume.
You Own The Phone Number and The Code
The entire system, from the Twilio phone number to the Python source code in your GitHub repository, is yours. There is no vendor lock-in.
Alerts When a Call Needs Review
A Slack message is sent with a call transcript and recording if the agent cannot resolve an issue, creating a clear feedback loop for improvement.
Connects Directly to Your Systems
Tickets are created directly in your helpdesk or CRM, like HubSpot or a custom platform, with structured data. No more manual data entry from voicemails.
What Does the Process Look Like?
Scoping and Setup (Week 1)
You provide examples of common support requests and grant API access to your CRM. We deliver a project plan and provision the Twilio phone number.
Core Agent Build (Week 2)
We build the conversation logic using Python and the Claude API. You receive daily call transcripts to review the agent's performance on test scenarios.
Integration and Testing (Week 3)
We connect the agent to your CRM and any internal APIs. You receive a dedicated test phone number to call and verify tickets are created correctly.
Go-Live and Handoff (Week 4)
We switch your live phone number to the AI agent. You receive a system runbook and a monitoring dashboard for tracking call volume and outcomes.
Frequently Asked Questions
- How much does a custom voice agent cost to build?
- The build price depends on the number of distinct call paths and required API integrations. A simple appointment setter is different from an agent checking real-time inventory. We scope this in a discovery call. After the one-time build, hosting and API costs are typically under $50/month, a fraction of an answering service.
- What happens if the agent misunderstands a caller?
- The agent is designed to 'fail gracefully'. If it cannot understand the user after two attempts, it provides a direct number for human support or offers to take a message. The full transcript and audio are flagged for review so we can improve the prompt or knowledge base. This prevents customer frustration loops.
- How is this better than a service like Talkdesk or a sophisticated IVR?
- Platforms like Talkdesk are full-stack contact centers for large teams with per-seat pricing. An IVR is a static menu tree. Syntora builds a lightweight, serverless agent that uses generative AI for fluid conversation and logic, integrated directly with your specific tools, without the high monthly cost or per-agent fees.
- Can the agent handle different languages or strong accents?
- Yes. We select a transcription model based on your primary customer base. Modern transcription APIs are very effective with a wide range of accents. For other languages, we can build separate flows, but each language is treated as a distinct build as it requires its own prompts and TTS configuration.
- How do we update the agent's knowledge base?
- The agent often pulls from a knowledge base we set up in a Supabase database. You receive a simple web interface to add, edit, or remove Q&A pairs. The changes are live within minutes, requiring no code. This lets you update pricing, hours, or policies yourself.
- What is the actual latency? Do callers notice a delay?
- The total 'ear-to-mouth' latency is under one second. Real-time transcription, a 500ms response from the Claude API, and 300ms for text-to-speech generation add up to a pause that feels natural in conversation. It is not perceived as an awkward system delay by most callers.
Ready to Automate Your Technology Operations?
Book a call to discuss how we can implement ai automation for your technology business.
Book a Call