Automate Logistics Tracking with Custom Voice AI
The top voice AI providers for SMB logistics are custom-built systems, not large SaaS platforms. They connect directly to your existing TMS or ERP without expensive per-seat licensing.
A custom voice system is designed for the specific commands and data fields your business uses. The scope depends on the number of load statuses you track and the complexity of your TMS integration. A system that only captures arrival and departure times is simpler than one that also parses detention reasons and lumper fees.
We built a voice check-in system for a 15-person freight brokerage. Their 100+ drivers now report status via a dedicated phone number instead of calling dispatchers. This automated data entry for 80% of their daily check-in calls and saved each of their 4 dispatchers about 90 minutes per day. The system was live in 3 weeks.
What Problem Does This Solve?
Many logistics companies first look at cloud transcription services like AWS Transcribe. They quickly find that these services only solve one part of the problem. You get a text file of what the driver said, but a dispatcher still needs to read it, find the load ID, and manually enter the update into your TMS. You have traded a phone call for a transcript that still requires manual work.
A regional 3PL with 25 employees tried to solve this with a visual IVR builder from Twilio. They spent two weeks dragging and dropping nodes to create a call flow. The system failed in production because it could not parse unstructured driver speech like, "Hey, it's Mike, I'm at the shipper for load A-B-one-two-three." The IVR expected structured keypad inputs, but drivers just talk. The project was abandoned after burning through $1,500 in platform credits.
These off-the-shelf tools fail because logistics tracking is not a generic customer service problem. It requires a system that understands industry-specific terms, validates inputs against a live database (your TMS), and handles the variety of accents and background noise from drivers on the road. A generic tool cannot provide this context-aware logic.
How Does It Work?
We start by provisioning a dedicated phone number using Twilio's Programmable Voice API. When a driver calls, the call is routed to a FastAPI service we deploy on AWS Lambda. This serverless architecture means you only pay for the seconds the system is actively processing a call.
Live audio is streamed to Anthropic's Claude 3 Sonnet API. We use a specific prompt engineered to extract structured data from the driver's speech: Load ID, Status (e.g., 'Arrived at Shipper', 'Departed Receiver'), and a Timestamp. This API call has a latency under 500ms and accurately extracts the correct data over 97% of the time, even with significant background noise.
Once the data is extracted, the FastAPI service validates it against your Transportation Management System. We write a direct integration to your TMS database, whether it's McLeod, TMW, or a custom system running on PostgreSQL. A successful update writes to the database in under 2 seconds. The entire process from the driver hanging up to the load status being updated in the TMS is less than 5 seconds.
A confirmation SMS is sent back to the driver via the Twilio Messaging API, confirming the update was received. We configure structured logging with structlog, sending all transaction data to a Supabase table. If the API error rate exceeds 3% in a 1-hour window, a webhook sends an alert to a designated Slack channel for immediate investigation.
What Are the Key Benefits?
Live in 15 Business Days
We complete the entire build, from discovery to deployment, in 3 weeks. Your drivers start using the system immediately, not after a long pilot program.
One-Time Build Cost
A single, fixed-price project. Your ongoing costs are just the direct AWS and Twilio usage, typically under $100 per month, with no per-seat fees.
You Own The Code
We deliver the full Python source code to your company's GitHub account. You are never locked into our service and have a permanent business asset.
Know About Failures in 5 Minutes
Automated monitoring sends a Slack alert if transcription accuracy drops or TMS updates fail. You learn about issues instantly, not hours later.
Integrates With Your Current TMS
We build a direct connection to your existing TMS or ERP. Your dispatchers see the updates in the system they already use all day.
What Does the Process Look Like?
Discovery and Data Mapping (Week 1)
You provide read-only access to your TMS and a list of status updates you need to track. We map the required data fields and define the voice command logic.
Core Logic and Voice Build (Week 2)
We build the FastAPI application, configure the Claude API for data extraction, and set up the Twilio phone number. You receive a working prototype to test.
TMS Integration and Deployment (Week 3)
We write the code to connect the voice system directly to your TMS database. The complete system is deployed to AWS and you get the full source code.
Monitoring and Handoff (Weeks 4-8)
We monitor system performance for 30 days after launch, tuning prompts as needed. At the end, you receive a runbook for ongoing management.
Frequently Asked Questions
- How much does a custom voice tracking system cost?
- Pricing is a fixed, one-time fee based on project scope. The primary factors are the number of distinct statuses to track (e.g., 'arrived', 'detention', 'departed') and the technical complexity of integrating with your specific TMS. A system with five statuses connecting to a well-documented SQL database is straightforward; a 15-status system connecting to a legacy AS/400 system requires more work. We provide a fixed quote after a 30-minute discovery call.
- What happens if a driver's speech can't be understood?
- If the AI cannot confidently extract the required data, the system has a fallback. It emails an audio file of the call and the raw text transcript to a designated dispatcher. This ensures no update is ever lost. This 'human-in-the-loop' process happens on fewer than 3% of calls and provides data for us to improve the system prompts during the initial monitoring period.
- How is this different from a virtual receptionist service?
- Virtual receptionists are designed to answer calls, take messages, and route to humans. They do not perform automated actions in other software. Our system is an automation engine. It understands logistics-specific language, extracts structured data from speech, validates that data against your TMS in real time, and writes the final update to your database without any human intervention.
- Does this work with different languages or heavy accents?
- Yes. The underlying language models from Anthropic are trained on a global dataset and perform well with a wide range of accents and dialects. For a client with a large number of Spanish-speaking drivers, we built a bilingual system that detects the language and applies the correct prompts, achieving over 96% successful automation for both English and Spanish calls.
- What are the ongoing maintenance requirements?
- The system is designed to run with minimal oversight. The AWS Lambda, Twilio, and Supabase components are fully managed. The only time you might need a developer is if you change your TMS, add a new status you want to track, or want to change the core logic. For a flat monthly fee, Syntora can handle this ongoing maintenance for you.
- Do we need our own AWS or Twilio accounts?
- We strongly recommend you create your own accounts. This ensures you have full ownership and control of your system and data. The setup process for both takes less than an hour, and we provide a checklist to guide you. If you prefer, we can host the system on our accounts and bill you for usage, but owning the infrastructure is the better long-term approach.
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