Automate Shipment Tracking Calls with a Custom AI Agent

Many logistics companies rely on a standard IVR phone tree, which only frustrates callers who want a simple answer. Customers repeatedly press '0' to bypass the menu because the system cannot understand a natural question like, "Is the shipment for Acme Corp going to make it to Dallas by Friday?" The IVR can only route calls; it cannot answer questions, leaving customer service representatives (CSRs) to handle every routine lookup.

Some teams try generic website chatbots, but these are disconnected from the core operational data. A chatbot from a platform like Intercom can pull from a knowledge base, but it cannot access your live TMS to check on shipment #BOL98765. The bot can only tell a customer how to track a package, not where their specific package is right now. This forces the customer to call anyway, defeating the purpose.

Even specialized telephony AI tools often fail because their logic is too rigid for the messy reality of logistics. These systems expect a perfectly formatted tracking number. If a caller provides a name or a purchase order number instead, the agent fails. The structural problem is that these tools are not built to orchestrate queries across multiple, disparate logistics systems. Answering a simple tracking question often requires checking the TMS, the WMS, and a specific carrier's portal. Off-the-shelf tools cannot manage this multi-step data retrieval process in real time.

The first step would be a data and process audit. Syntora would map every system needed to answer a tracking inquiry, from your TMS and WMS APIs down to carrier portals that might require browser automation. We would analyze a sample of 100 recent call recordings or transcripts to identify the most common questions and phrasings your customers use. This audit produces a clear plan for what data the AI agent needs and how it will get it.

The technical approach would use a FastAPI service running on AWS Lambda to create a voice-driven workflow. When a call comes in, a speech-to-text service converts the audio. The Claude API then parses the text to identify the customer's intent and extract key information like a tracking number or customer name. The Python-based Lambda function then executes a series of queries: first to your TMS to identify the shipment and carrier, then to the carrier's API for the live location. The final status is converted back to natural language for the caller.

The delivered system is a dedicated phone number for your customers to call for status updates. The agent answers the call, provides the information, and logs the interaction in your helpdesk. If an inquiry is too complex for the agent to handle (like a damage claim), the system intelligently transfers the call to a live CSR, passing along the full context so the customer does not have to repeat themselves. The system would handle over 80% of routine tracking calls, freeing up your team for high-value work.