Development of an AI assistant for faster analysis of incidents and change requests
Speed up the ticket processing time
Challenges
Inconsistent Data Sources: Standardization of data to make information from different source systems searchable
Data Volume Optimization: Reduce the amount of data to the bare minimum without losing important information
User Adoption Hurdles: Show users how to use it so that they recognize the added value of the solution
Solutions
Efficient Data Pipeline: Development of a Data Engineering pipeline in Python
User-Friendly Interface: Access the AI Assistant via React Frontend
Scalable Cloud Deployment: Deployment of RAG Use Case on Azure
Values
Faster Ticket Processing: Tool for users to process the volume of tickets more easily and quickly
Branded, User-Centric Interface: User friendly web interface with company branding and daily updated data
Automated Ticket Intelligence: Automated summarization and classification of tickets
Roles
AI Engineer, Cloud Engineer, Data Engineer, Project Manager
Technologies
Sectors
Telco & IT