Revolutionizing Customer Service Efficiency with AI

Find out how large language models and process AI are setting new standards in vehicle logistics. Advanced AI technology and powerful neural networks make it possible to automate routine requests and shorten response times. This way, companies increase both employee productivity and customer satisfaction.

Use Case

Summary

• In vehicle logistics, LSPs (Logistics Service Providers) face challenges like handling numerous emails daily and long response times.
• In our use case, a Customer Service Center handles approximately 100,000 inquiries annually, primarily via email, with seven employees responsible for managing these dealer-to-dealer transport requests.
• Often these emails have the same content, but the format is very diverse (unstructured data). Anyone who tries to put this into a meaningful form using traditional methods faces a major challenge. This is where our AI assistant comes in.
• Among other things, our AI assistant can formulate an appropriate response (language, style, tonality), to recognize identification numbers in the request (even if they were only partially mentioned in the request) and retrieve them from the system in full length in its response, for example.
• By automating the processing and replying to these emails, our Customer Service AI Assistant reduces the workload on human agents and improves response times.

How It's Done

• Data Collection: Gathering relevant data to train the model.
• Contextual Understanding: Ensuring the model processes context-specific queries using Process AI.
• Knowledge Grounding: Integrating real-time data through APIs, local code execution or reading full files.

Despite prompt size limitations, techniques such as using a vector database help pull only relevant information, ensuring efficient and accurate responses. Neural networks play a critical role in understanding and generating appropriate responses.

Did You Know?

• Less overwhelmed employees thanks to AI: A study by Deloitte Digital found that companies already using generative AI report that their employees are 35% less frequently overwhelmed by the flood of information during customer conversations. 
• Job satisfaction in customer service is often very low, and turnover rates are high. According to the Deloitte study, leading service companies recorded an annual turnover rate of 52% in 2023. Through automation, solution suggestions, summaries of email threads, and filtered information, AI is making the tasks of service teams more attractive.