Build a Custom Voice AI Agent for Your Logistics Dispatch
The best voice AI provider for logistics builds a custom system you fully own. This avoids per-seat fees and vendor lock-in from off-the-shelf platforms.
A custom voice agent’s complexity depends on the number of systems it must connect to and the logic of the call flow. Integrating with a single, modern TMS with good API documentation is a straightforward build. Connecting to a legacy TMS, a GPS provider, and a CRM simultaneously requires more complex integration code.
We built a voice AI dispatch agent for a 7-person regional trucking company. They managed 50 drivers entirely by phone and a shared spreadsheet. The system went live in 4 weeks, reducing the time to assign a new load from an average of 8 minutes to 90 seconds.
What Problem Does This Solve?
Many logistics companies first try no-code tools like Voiceflow or Twilio Studio. These are effective for simple phone trees but fail when real-time database lookups are needed. A dispatcher needs to query a Transportation Management System (TMS) to confirm a load ID. The platform's basic HTTP request module cannot handle the custom authentication or data re-formatting that most TMS APIs require, leading to brittle connections that break.
A common failure scenario involves a driver calling to get their next assignment. The Voiceflow app asks for their driver ID. The app sends the ID to the TMS, but the TMS API returns a nested JSON object. The no-code tool cannot parse this structure to extract the load number and destination address. The workflow fails, the driver gets a generic error message, and they have to call a human dispatcher anyway, defeating the purpose.
Larger platforms like Amazon Connect are powerful but require a dedicated DevOps team to manage. A 15-person company doesn't have the staff to configure IAM roles, VPCs, and Lambda triggers. They are forced to hire an expensive consultant to set it up, and another one to change the call script six months later. This creates a new dependency that is just as restrictive as a SaaS vendor.
How Does It Work?
First, we map your entire dispatch call flow, diagramming every question, potential answer, and system query. We use the Claude API for natural language understanding, allowing drivers and brokers to speak normally instead of navigating rigid menus. This system extracts key entities like load numbers, driver IDs, and timestamps from conversational speech with over 95% accuracy.
We write a central routing service in Python using the FastAPI framework. This service acts as the brain of the operation. It uses the httpx library for asynchronous calls to your TMS and any other external APIs, like a GPS provider. All call data and interaction logs are stored in a Supabase Postgres database, creating an audit trail for every dispatch action. This custom code handles your specific API authentication, whether it is OAuth2 or a simple API key.
For the voice and telephony layer, we use Twilio's Programmable Voice API. We do not use their drag-and-drop studio. Our FastAPI service receives the call, processes the real-time audio stream, and sends back synthesized speech. This entire service is deployed on AWS Lambda, which costs under $30 per month to handle 5,000 two-minute calls. The P99 response latency for an API lookup and verbal response is under 800ms.
Monitoring is built-in using structlog for structured JSON logging. These logs are sent to a monitoring service. We configure alerts that trigger if the error rate from your TMS API exceeds 5% in a 10-minute window, or if call duration unexpectedly drops. This lets us detect and fix integration issues before your drivers notice a problem.
What Are the Key Benefits?
Live in 4 Weeks, Not 6 Months
From our first call to a production-ready system in under 20 business days. Your dispatch process gets faster immediately, without a quarter-long implementation project.
Own the System, Stop Paying Per Call
After a one-time build, your only recurring cost is for cloud hosting, not a per-user or per-minute SaaS fee. Increased call volume lowers your per-call cost.
Your Code, Your GitHub, Your Control
We deliver the complete Python source code to your private GitHub repository. You are never locked into Syntora and can have any developer extend the system.
Alerts When Your TMS Fails
The system monitors its own connections. You get an immediate alert if your TMS API goes down, so you are not troubleshooting based on driver complaints.
Integrates with Your Legacy TMS
Because we write the integration code from scratch, we can connect to any system with an API, including older, industry-specific transportation management systems.
What Does the Process Look Like?
Discovery and API Access (Week 1)
You provide documentation and credentials for your TMS and any other systems. We deliver a detailed call flow diagram and a technical plan for approval.
Core Logic and Integration Build (Week 2)
We build the core FastAPI application and the custom integration code. You receive a staging URL to test the API endpoints directly.
Voice Integration and Deployment (Week 3)
We connect the application to a live phone number and deploy it to AWS Lambda. You receive the number to begin user acceptance testing with your team.
Monitoring and Handoff (Week 4)
We configure production monitoring and alerting. You receive the complete source code, documentation, and a runbook covering common operational tasks.
Frequently Asked Questions
- How is the project price determined?
- Pricing is based on two factors: the number of unique call flows (e.g., driver check-in is one flow, broker inquiry is another) and the number of external systems to integrate. A single flow connecting to a well-documented TMS API is the baseline. Adding more flows or integrating with a second system like a GPS provider increases the scope. We provide a fixed price after our initial discovery call.
- What happens if our TMS API is down?
- The voice agent is built to fail gracefully. It detects the API connection failure and plays a message informing the caller that the system is temporarily unavailable. The system can be configured to forward the call to a human dispatcher's cell phone as a fallback for critical inquiries. Every failure is logged, and an alert is sent to your technical contact.
- How is this different from a service like Talkdesk or Aircall?
- Talkdesk and Aircall are comprehensive call center platforms sold with per-seat licenses for human agents. Syntora builds a specific, unmanned AI agent to fully automate a single, repetitive business process like logistics dispatch. We do not provide a user interface for agents; we build a system that replaces the need for a human to handle that specific type of call.
- Can the system handle drivers with strong accents?
- Yes. We use transcription models that are trained on thousands of hours of diverse, global audio data. During testing, we can use synthesized audio samples with various accents to benchmark and confirm accuracy for your specific use case. If the system's confidence score for a key piece of information is low, it will politely ask the caller to repeat it.
- What if our dispatch process needs to change in the future?
- You receive the full Python source code, so any developer can modify the system. The call flow logic is contained in specific, well-documented files. For minor changes like updating a voice prompt, we provide a runbook with clear instructions. For major changes, like adding a new API integration, we can scope a follow-on fixed-price project.
- Does the AI voice sound robotic?
- No. We use modern text-to-speech (TTS) APIs that generate natural, human-like voices. We can select from a library of different voices and accents to find one that aligns with your company's brand. The pacing and intonation are also adjustable to ensure the interaction is clear and professional, not frustrating for your callers.
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