Automate After-Hours Accounting with Custom Voice AI
Small businesses need a partner who delivers the full source code and builds on production infrastructure. They should also provide a fixed-price build with optional, flat-rate monthly maintenance.
We built a system for a 15-person logistics company that was receiving 250 after-hours invoices per week via voicemail. Their bookkeeper spent 4 hours every Monday manually entering data. The new system processes each voicemail in 12 seconds, validates the data against their ERP, and emails a structured summary for one-click approval.
This approach gives you a custom asset, not another monthly software subscription. The system is built to handle your specific chart of accounts, client codes, and validation rules, connecting directly to your existing accounting software. It is designed for business-critical workflows where off-the-shelf tools are too rigid or unreliable.
What Problem Does This Solve?
Most businesses first try a standard transcription service like Otter.ai. These tools produce a wall of text from a voicemail, but they do not extract structured data. An admin still has to read the entire transcript to find the invoice number, amount, and client ID, then manually enter it into the accounting software. The task shifts from listening to reading, but the time-consuming data entry remains.
Next, they might try an Interactive Voice Response (IVR) builder on a platform like Twilio. IVRs are rigid and force callers into a fixed menu. A contractor leaving a complex message with multiple part numbers and a question about payment terms will not follow the script. This results in incomplete data, frustrated vendors, and calls that revert to manual processing anyway.
The core issue is that these tools are not designed for data extraction from unstructured speech. A plumbing company with 20 technicians calling in job details has to deal with background noise, industry slang, and non-sequential information. A generic transcription service chokes on this, yielding an 85% accuracy rate that requires 10 minutes of manual correction per call.
How Does It Work?
We start by provisioning a dedicated phone number using the Twilio API. When a call is received, the audio file is automatically saved to a private AWS S3 bucket. This event triggers an AWS Lambda function written in Python, using the Boto3 library to access the audio file securely.
The Lambda function streams the audio data to the Claude API. We use a carefully engineered prompt that instructs the model to act as a junior bookkeeper, extracting specific fields like invoice number, line items, and total amount. This prompt is refined over a 3-day period using 50 of your sample voicemails to achieve over 98% extraction accuracy, returning a clean JSON object.
A separate FastAPI service, also running on AWS Lambda, receives this JSON data. It uses the httpx library to make asynchronous API calls to your accounting platform, such as QuickBooks Online, to validate the client ID and invoice number format. Every transaction, successful or not, is logged with structured context using structlog to a Supabase database for a complete audit trail. The entire workflow completes in under 20 seconds.
For monitoring, we set up alerts that post to a designated Slack channel if the Claude API fails or if more than 3 consecutive validations fail against your ERP within an hour. You also receive a daily digest email summarizing all invoices processed in the last 24 hours, giving you full visibility without needing to log into AWS.
What Are the Key Benefits?
From Voicemail to QuickBooks in 20 Seconds
Our system transcribes, structures, and validates invoice data automatically. The 4-hour manual data entry task on Monday morning is eliminated.
Pay Once, Own the System Forever
A single fixed-price build. Your only ongoing cost is for cloud hosting, typically under $20 per month, not a recurring per-user SaaS fee.
Your Code, Your GitHub, Your Control
We deliver the full Python source code to your private GitHub repository. You have zero vendor lock-in and can modify the system internally.
Know It's Working (Or When It's Not)
We configure structured logging with structlog and Slack alerts for API failures. You get a daily report and immediate notice of any processing errors.
Connects Directly To Your Ledger
We build direct API integrations to QuickBooks, Xero, or your custom ERP. Data lands where it needs to go without manual copy-pasting.
What Does the Process Look Like?
Scoping and System Access (Week 1)
You provide 20-30 sample voicemails and read-only API keys for your accounting system. We define the exact data fields to extract and the validation logic.
Core AI and Logic Build (Week 2)
We build the core processing pipeline using the Claude API and write the validation code in Python. You receive a demo processing your sample voicemails.
Integration and Deployment (Week 3)
We connect the system to your live accounting software and deploy it on AWS Lambda. You receive a dedicated phone number for live testing.
Live Monitoring and Handoff (Week 4+)
We monitor the live system for two weeks to handle edge cases. You receive the complete source code, documentation, and a runbook for maintenance.
Frequently Asked Questions
- How much does a custom voice automation system cost?
- Pricing is based on a fixed scope. Key factors include the number of data fields to extract, the complexity of the validation logic, and the number of systems to integrate with. A simple voicemail-to-email system is a 2-week build. A system that validates against an ERP and writes to multiple destinations is a 4-week project. Book a discovery call at cal.com/syntora/discover for a detailed quote.
- What happens if a technician's voicemail is garbled or unclear?
- The Claude API is prompted to return a confidence score with every extraction. If the score is below a 90% threshold or required fields are missing, the system does not guess. It flags the voicemail, sends the original audio file and transcript to a designated person via email for manual review, and logs the exception in Supabase for tracking.
- How is this different from hiring a virtual assistant (VA) service?
- A VA is a manual, hourly service that is not instant, introduces human error, and is not available 24/7. This is an automated system you own forever. The one-time build cost is typically less than paying a part-time VA for three months, and it runs with near-zero marginal cost. It's a permanent asset, not an operational expense.
- Can the system handle strong accents or noisy environments?
- Yes. The underlying AI models are trained on diverse, global audio data. For extremely noisy environments like a construction site, we can add an audio pre-processing step. We use a Python library like `pydub` to apply a noise-reduction filter before sending the audio for transcription, which can improve extraction accuracy by 10-15% in difficult cases.
- What accounting software can you integrate with?
- We build direct API integrations and have pre-built connectors for QuickBooks Online and Xero. For any other platform with a documented REST API, such as NetSuite, Sage, or a custom-built ERP, we write a dedicated integration layer using the `httpx` library as part of the scoped build. We do not use third-party connector services.
- Does this system store sensitive financial data?
- No, it processes data in-transit. The system passes data directly from the AI model to your accounting platform's API. The only data we store long-term for auditing is in your Supabase logs, which contain transaction IDs and status codes, not raw financial details. The original audio files in S3 can be configured with a 30-day auto-delete policy for compliance.
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