Accelerating Scientific Communication with AI:

A cartoon illustration of a robot with a headset, dressed in a lab coat and tie, labeled as LabBot, a Toxicology Research Assistant.

How a custom chatbot transformed inquiry handling and operational efficiency at the Toxicology Research Laboratory, University of Illinois Chicago.

  • The Toxicology Research Laboratory (TRL) at the University of Illinois Chicago is a nationally recognized research facility with over 30 years of expertise in preclinical safety and efficacy studies. With a wide array of services—from neurobehavioral toxicity to pharmacokinetics and genomic research—TRL receives a high volume of complex inquiries from academic researchers, pharmaceutical partners, and clinical collaborators.

    Despite its advanced data systems and scientific infrastructure, TRL lacked a streamlined way to handle incoming questions about services, study protocols, and data capabilities. Staff were spending valuable time manually responding to repetitive inquiries, and potential collaborators often faced delays in getting the information they needed.

  • Design and deploy a conversational AI chatbot that could:

    Handle frequently asked questions about TRL’s services and capabilities

    • Guide users to relevant resources (e.g., study types, data systems, support services)

    • Reduce manual workload for TRL staff

    • Maintain scientific accuracy and professionalism in tone

    • 📈 40% reduction in manual inquiry handling within the first 60 days

    • ⏱️ Faster response times for collaborators and researchers

    • 🧠 Improved clarity in service navigation, especially for complex study types

    • 💬 Positive feedback from internal staff and external partners on usability and tone

    • 🔬 More time freed for scientists to focus on research, not admin

  • Boots On The Ground AI partnered with TRL to build a custom chatbot tailored to the lab’s unique needs. The chatbot was trained on TRL’s service offerings, technical terminology, and institutional tone. Key features included:

    • Dynamic FAQ handling for study types, data systems (e.g., LABCAT), and statistical tools

    • Smart routing to guide users to specific departments (e.g., biostatistics, veterinary pathology)

    • Context-aware responses that adjusted based on user type (e.g., researcher vs. sponsor)

    • Embedded links and document previews for protocols and service descriptions

    The chatbot was deployed on TRL’s website with a clean interface and integrated seamlessly into their existing digital ecosystem.