Reinventing Helpdesk Support with AI Driven Technology

GLIMR

In a strategic move to enhance customer service and streamline internal policy inquiries, Microsoft engaged Launch to develop a cutting-edge, AI-driven solution aimed at reducing support ticket volumes and automating policy responses. This collaboration led to the development of two innovative chatbots: the GLIMR Chatbot and the Product Loan and Giveaway (PL&G) Chatbot, crafted to streamline support queries with smart self-service options and designed to effortlessly automate policy responses. Both chatbots, powered by cutting-edge Semantic Kernel technology and Azure Open AI, represent a major advancement in self-service capabilities and the conservation of engineering resources.   

Tackling Support System Congestion 

Our client faced a dual-faceted challenge that was impeding operational efficiency. Firstly, a significant portion of their support tickets comprised basic user instruction queries, which heavily congested their support system. Secondly, frequent inquiries related to the company’s product loan and giveaway program policies required time-consuming, manual responses from senior personnel. The ongoing problem necessitated a sophisticated solution to enhance efficiency and automate responses, enabling staff to redirect their focus toward higher-value activities. 

Leveraging AI for Operational Excellence  

Launch's reputation for harnessing technology and AI solutions to enhance client efficiency and streamline workloads, augmented by our successful track record of partnerships with Microsoft, positioned us as the ideal partner for our client's needs. Our commitment to delivering swift, streamlined solutions, along with our capability to standardize these innovations for wider implementation across teams, aligned impeccably with the client’s goals.  

Launch’s approach involved the design and implementation of tailor-made AI chatbots, each serving distinct functions within the organization: 

1.       GLIMR Chatbot 

This chatbot was engineered to handle initial support queries, guiding users through self-service options before escalating to human-handled support tickets. It specifically targeted reducing ticket congestion by directly addressing the common user instruction queries through automated responses. 

2.       Product Loan and Giveaway Program Chatbot 

Developed to automate responses to policy-related questions for the company’s product loan and giveaway program, this chatbot streamlined processes and eliminated the need for manual interventions by senior personnel. 

The Tangible Benefits of AI-Driven Solutions:  

·      Efficiency Improvement 

The deployment of these AI chatbots markedly enhanced customer support efficiency by reducing the volume of basic support tickets and automating the dissemination of policy-related information. 

·      Rapid Deployment and Scalability 

The project showcased Launch’s ability to rapidly deploy complex AI solutions, having the solution up and running in six weeks. The implemented system proved scalable, with more than 7,000 users adopting the new tools, reflecting both its effectiveness and wide acceptance. 

·      Enhanced Support Experience: Reflecting on AI's Positive Impact  

Following the deployment, employees and customers reported a noticeable improvement in accessing support and policy information, appreciating the speed and efficiency of the new system. The solution effectively freed up time and resources, allowing the company to allocate its workforce to more specialized tasks. The project not only exemplified rapid and efficient implementation but also set a benchmark for scalable, high-quality AI solutions that enhance operational efficiency without sacrificing performance.  

Strategic Impact 

The introduction of the GLIMR and Product Loan and Giveaway Program chatbots set a new benchmark for AI solutions in operational efficiency for our client. This project exemplified rapid and effective implementation, proving that high-quality AI solutions can enhance operational efficiency without compromising performance.  

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