Custom Voice AI for Financial Query Answering
Most voice AI providers offer large-scale call center solutions, not SMB-focused systems. Syntora builds custom voice AI agents for financial query handling for small teams.
We built a voice agent for a 7-person accounting firm that received 50 client calls per day. The system automated answers for invoice status and payment due dates, reducing human-handled call volume by 60% within the first month of operation.
These systems connect directly to your accounting software to answer specific client questions in real-time. They are not generic phone trees but intelligent agents trained on your most common inquiries. A typical build handles the top 5-10 questions that consume your team's time.
What Problem Does This Solve?
Many SMBs first try a standard Interactive Voice Response (IVR) system from their phone provider. These systems can route calls by asking callers to press '1' for billing or '2' for support, but they cannot answer a question. When a client asks, "What is the status of invoice 12345?" the IVR can only forward the call, not fetch the answer.
Next, they look at contact center platforms like Five9 or Talkdesk. These are powerful but built for 100-seat call centers, with per-agent, per-month pricing that is prohibitive for a 15-person business. You end up paying for a massive feature set when you only need one capability: automated answering. The contracts are often multi-year commitments for a system that requires a dedicated team to manage.
A technical founder might attempt a DIY solution using Twilio's APIs. While powerful, this path requires a full-time engineering effort. Piecing together speech-to-text, a language model like Claude, business logic, and a secure integration to QuickBooks is a multi-month software project. It is not a configuration task; it is a ground-up development project that requires deep expertise in multiple domains.
How Does It Work?
Our process begins by analyzing your call logs or having you list the top 10 most frequent, repetitive financial questions your team answers. We then request read-only API access to your financial platform, typically QuickBooks Online, Xero, or a specific ERP. This access allows the system to fetch live data to answer queries accurately.
The core of the system is a Python service built with FastAPI. When a call is received, the audio is transcribed in real time. This text is sent to a purpose-built prompt on the Claude API to classify the caller's intent, such as 'invoice_status_query' or 'request_payment_link'. This classification achieves over 95% accuracy on in-scope questions after tuning.
Once the intent is classified, the FastAPI service makes a secure API call to your financial system to retrieve the necessary data. For an invoice status query, it might fetch the amount, due date, and status. The raw data is then passed to a second Claude API call, which formats it into a natural, conversational sentence. This text is converted to speech and played back to the caller. A full cycle, from spoken question to audio answer, completes in under 3 seconds.
We deploy the entire system on AWS Lambda, so you only pay for compute time when calls are active. For a business handling up to 1,000 queries per month, hosting costs are typically under $50. We use structlog for detailed logging of every interaction. If the AI's confidence in understanding a query falls below a 90% threshold, the system automatically offers to transfer the call to a human.
What Are the Key Benefits?
Answer Client Calls in 3 Seconds, 24/7
The system provides immediate, accurate answers to common financial questions. It operates outside business hours, reducing morning call queues and client frustration.
One-Time Build Cost, Not Per-Agent Fees
We deliver a finished system for a fixed price. You avoid recurring monthly SaaS fees that increase as your team grows.
You Own the Production Code
We deliver the complete Python source code to your company's GitHub repository. You have full control and no vendor lock-in.
Fails Gracefully to a Human
If the AI is ever uncertain about a caller's request, it automatically offers to transfer them to a team member. This prevents incorrect answers and protects the client experience.
Direct Integration with QuickBooks and Xero
The system connects directly to your existing accounting software using secure, read-only API keys. Answers are always based on the most current data.
What Does the Process Look Like?
Query Scoping (Week 1)
You provide a list of the top 5-10 repetitive questions your team answers. We deliver a technical plan outlining the logic and data required for each answer.
Core AI Build (Week 2)
We build the FastAPI service, Claude API prompts, and core logic. You receive a demo phone number to test the basic question-answering flow with static data.
Integration & Deployment (Week 3)
You grant read-only API access to your financial platform. We deploy the system on AWS Lambda, connect it to your data, and route your support number.
Monitoring & Handoff (Weeks 4-5)
We monitor live call transcripts for two weeks to tune accuracy. You receive the full source code, AWS credentials, and a runbook for future maintenance.
Frequently Asked Questions
- What factors determine the project cost and timeline?
- The primary factors are the number of distinct questions the system must answer and the quality of your accounting software's API. A system handling 5 query types for QuickBooks Online is a standard 3-week build. Supporting 15 query types for a legacy, on-premise ERP with a SOAP API would require a more complex scope.
- What happens if the AI misunderstands a client?
- The system is designed to fail safely. If its confidence score in understanding the request is below 90%, it will not attempt to answer. It responds by saying it cannot handle the request and offers to immediately connect the caller to a human. This prevents client frustration from bad answers and ensures complex issues reach your team.
- How is this different from a basic phone tree?
- A phone tree forces callers through a rigid menu using button presses. Our system uses natural language; a client can simply ask their question as they would to a person. It directly answers the query by fetching live data from your financial system, rather than just routing the call to a department.
- How do you ensure our financial data is secure?
- We exclusively use read-only API credentials, so the system can never modify your data. The entire application is deployed within your own AWS account, meaning no sensitive information ever passes through Syntora's infrastructure after the handoff. All communication between services uses TLS 1.2 encryption.
- Can it understand different accents or noisy calls?
- We use modern speech-to-text models trained on a vast and diverse dataset, which provides high accuracy across many accents. For calls from extremely noisy environments, like a car with the windows down, transcription quality can degrade. The system's built-in confidence scoring helps detect these situations and route the call to a human agent.
- Can we customize the voice and personality?
- Yes. The text-to-speech engine supports dozens of different voices and speaking styles. The personality and tone of the responses are controlled by the Claude API system prompt. We can adjust this prompt during the build to make the voice agent sound more formal, more conversational, or match a specific brand voice you define.
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