PROBLEM STATEMENT
A forward-thinking legal firm faced challenges in managing its internal help desk operations, which included handling a wide range of queries from staff regarding legal procedures, document management, IT support, and administrative tasks. To enhance efficiency and provide timely support, the firm introduced an innovative Large Language Model (LLM)-based automation solution for its help desk.
sSOLUTION
The firm developed and deployed an LLM-powered chatbot designed to understand and process natural language queries from staff. This chatbot was integrated into the firm's existing internal communication platforms, offering a seamless interface for employees to access support. It was trained on a comprehensive dataset, the firm's internal knowledge base, procedural manuals, and common IT troubleshooting guides, ensuring a broad understanding of the firm's operations.
To automate the resolution of common inquiries, reducing the manual workload on help desk staff.
To provide instant, accurate responses to support queries, improving staff satisfaction and productivity.
To create a scalable solution capable of evolving with the firm's growing needs and complexities
Objectives
Implementation
Phase 1: Data Compilation and Model Training: Assembled extensive datasets covering all areas of potential queries and used them to train the LLM, focusing on understanding legal terminology, procedural nuances, and common IT issues.
Phase 2: Chatbot Development and UI Integration: Developed the chatbot with an emphasis on user experience, ensuring it could easily be accessed via the firm's existing digital tools and platforms.
Phase 3: Testing and Feedback Loop: Rolled out the chatbot in a controlled environment to gather user feedback and identify areas for improvement, ensuring the solution accurately addressed user needs.
RESULTS
Reduced Response Times: The chatbot provided immediate answers to common queries, reducing the average response time from hours to seconds.
Decreased Workload on Staff: Automated handling of routine inquiries resulted in a 40% decrease in manual tickets for the help desk team, allowing them to focus on more complex issues.
Enhanced Employee Satisfaction: Staff reported higher satisfaction levels due to the speed and accuracy of support provided, contributing to an overall increase in productivity.