A customized AI agent that answers incoming client inquiries about DOT drug-testing compliance — instantly, consistently, and with a clear handoff to a human when it matters.
Businesses that employ commercial drivers ask the same compliance questions again and again: when a test is required, what happens after a positive result, who needs to be in the testing program. Each inquiry was answered by hand, which meant delays for the client and inconsistent wording from one response to the next.
The goal was to shorten response times and standardize answers on a topic where precision matters — without pretending a chatbot can replace a compliance professional.
I built a custom AI agent that greets clients on the web, answers common DOT drug-testing questions in plain language, and escalates anything ambiguous or case-specific to a person. It combines a lightweight HTML/CSS front end, Java-based logic, and an AI model connected through an API.
Answers are drawn from a curated knowledge base built on published DOT and FMCSA drug-testing requirements, rather than the model's general memory.
The agent explains requirements in everyday terms and asks a clarifying question when a request is too broad to answer safely.
The agent doesn't give legal determinations, doesn't ask for sensitive personal details, and hands off to a human whenever a question turns on specific facts.
Conversations that escalate are reviewed so the knowledge base and prompts improve over time.
In a regulated domain, the most important feature of an AI assistant is knowing what it shouldn't answer. Most of the design effort went into defining the boundary — what the agent handles confidently, what it flags, and what it routes to a person — and that boundary is what made the tool trustworthy enough to put in front of clients.