Accelerating Customer Support Ticket Resolution with a RAG-powered Solution for Studytube

Company Name

Studytube

Location

Netherlands

Industry

Educational Technology

Services

AI and ML Services

Client

Studytube is the #1 corporate learning platform for organizations and employees that helps maximize time savings in organizational learning.

Challenge

The client’s customer service team had to search for answers in the knowledge base manually, spending lots of time and manual effort. Studytube needed a way to automate the search process and improve the overall response speed of the team to improve both operational efficiency and customer satisfaction.

Solution

DataArt developed a GenAI-powered RAG solution to help Studytube customer service agents automate replies to certain customer inquiries. The tool drafts answers to specific customer questions, taking into account data stored in the FAQs and other documents available. It generates the most optimal response on the basis of given prompts and response parameters with the help of Claude 3, while also providing information about documents used as reference. Support agents can edit the suggested answer before sending.

Attaining high accuracy and usability of quoting the source documents was the main challenge. The model also had to be trained to tell the user when it does not have the answer, or the information is absent. Prompt engineering was applied to overcome the challenge – response examples and a set of instructions were provided to the model so that it can draft the most relevant response.

Technologies

Bedrock

Lambda

OpenSearch

ECR

ECS

DynamoDB

API Gateway

Kinesis Firehouse

Step Functions

Outcomes

Achieved 90% accuracy of the generated responses
Created a workflow so responses can be sent to any relevant channel (email, Slack, etc.)
Enabled responses to be generated in different languages, even though the knowledge base is in Dutch-only
Delivered responses in 5 seconds or less, greatly reducing previous response times

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