Optimizing Customer Support with AI in AstroEngine Research

Engineering-related applied scientific research - AstroEngine Research *1

Optimizing Customer Support with AI in AstroEngine Research

AstroEngine Research deals with a large number of technical inquiries from clients every day. Prior to implementing Deskhero, their support team was inundated with the volume of tickets and struggled to provide timely responses. With Deskhero's ticket management and AI capabilities, the company can now efficiently categorize and prioritize tickets, ensuring that urgent issues are addressed promptly.

The AI-powered knowledge base has been instrumental for AstroEngine Research. By leveraging OpenAI Embeddings from previous tickets, knowledge base articles, uploaded files, and scraped website data, Deskhero suggests relevant content to the support team. This feature has drastically cut down the time spent on researching and drafting responses.

Deskhero's AI also enhances the search results within the platform. When the support team searches for information to resolve a ticket, the AI uses embeddings to find the most relevant content. This feature has significantly improved the accuracy and speed of information retrieval.

By using Deskhero's REST API, AstroEngine Research has integrated the platform with their existing systems. This integration has streamlined their workflow and improved data consistency across different platforms.

Since implementing Deskhero, AstroEngine Research has seen a significant improvement in their support team's efficiency and customer satisfaction. The advanced AI capabilities have enabled the team to manage a high volume of tickets effectively and provide accurate, timely responses.

 

How does Deskhero's AI categorize and prioritize tickets?
Deskhero's AI uses OpenAI Embeddings to analyze the content of the tickets. It then categorizes and prioritizes them based on their urgency and relevance.

How does the AI-powered knowledge base work?
The AI-powered knowledge base leverages OpenAI Embeddings from previous tickets, knowledge base articles, uploaded files, and scraped website data to suggest relevant content to the support team.

How has Deskhero improved the search results within the platform?
Deskhero's AI uses embeddings to enhance the search results within the platform. It analyzes the search query and finds the most relevant content from the knowledge base, previous tickets, uploaded files, and scraped website data.

 

* This article provides an example of how a fictive company in the Engineering-related applied scientific research industry is using Deskhero. Sign up now for free to discover how it can benefit your own organization.