RailLoad Solutions receives hundreds of support tickets daily, ranging from technical issues to service inquiries. With Deskhero, they can efficiently manage these tickets using the platform's structured data lists and kanban board. The AI capabilities help categorize and prioritize these tickets based on their urgency and relevance, thus improving response times.
Deskhero's AI also enhances RailLoad's knowledge base by generating articles from uploaded files such as policies, manuals, and presentations. This feature allows the company to provide comprehensive and up-to-date information to their customers, reducing the number of support tickets and improving self-service capabilities.
The AI-powered comprehensive search bar provides quick and accurate results, helping both customers and support agents find relevant information faster. This feature uses OpenAI embeddings from previous tickets, knowledge base articles, and other data sources to deliver the most relevant content.
Furthermore, Deskhero's AI generates suggested replies for support agents based on the context of the customer's inquiry and the company's past responses. This feature not only speeds up the response time but also ensures consistency and accuracy in the company's communications.
Finally, RailLoad uses Deskhero's REST API to integrate the platform with their existing systems, creating a unified and efficient customer support ecosystem.
How does Deskhero's AI prioritize support tickets?
Deskhero's AI uses OpenAI embeddings to understand the context and urgency of each ticket. It then categorizes and prioritizes them accordingly, ensuring that critical issues are addressed promptly.
How does Deskhero's AI enhance the knowledge base?
Deskhero's AI can generate knowledge base articles from uploaded files like policies, manuals, and presentations. This feature keeps the knowledge base updated and comprehensive, improving self-service capabilities.
How does Deskhero's AI generate suggested replies?
Deskhero's AI uses OpenAI embeddings from previous tickets, knowledge base articles, and other data sources to understand the context of the customer's inquiry. It then generates suggested replies based on this understanding and the company's past responses.
* This article provides an example of how a fictive company in the Railcar Loading & Unloading industry is using Deskhero. Sign up now for free to discover how it can benefit your own organization.
