ITEA is the Eureka Cluster on software innovation
ITEA is the Eureka Cluster on software innovation
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Tickota, the solution for ticket routing and expert assignment

Project
20003 OMD
Type
New product
Description

Tickota is a software tool that helps the service provider to use their resources effectively, to provide agile solutions, to conserve their knowledge base, to allocate each call unmistakably to the corresponding expert, as well as in the solution of the particular problem at hand.This shortance the assignment time and reduces the cost of operations, avoid repetitions. Increasing the overall efficiency.Tickota increases customer satisfaction.Tickota predicts completion time of ITSM tasks, an classifies priority/urgency of a ticket, thereby minimising response times and reducing SLA penalties.

Contact
Demet Seyhan (EXPERTEAM)
Email
demet.seyhan@experteam.com.tr
Research area(s)
ITSM systems, Artificial Intelligence, Machine Learning, Ticket Routing Models, Recommendation Models, Assignment Models
Technical features

An Artificial Intelligence-supported system has been designed to predict the resolution times of incoming Ticket requests for IT service software and to recommend the most appropriate experts for the solution. Regression, regularization, classification algorithms and natural language processing techniques are used in Tickota model. Our model can provide customer-oriented forecasting results with high success rates as below. • Completion times • The most suitable specialist • Ticket's priority • Type of Issue

Integration constraints

System architecture involves microservice structure. Integration possibilities currently involve webservices, APIs, model training are required.

Targeted customer(s)

Tickota is primarily developed for own customers to reduce cost internally. Remote working conditions can make our product attractive for similar ITSM companies in our network. Besides this primary market, we have some %50 companies in Turkiye that are listed in Oracle's partner database.

Conditions for reuse

Proprietary Licensing

Confidentiality
Public
Publication date
13-11-2024
Involved partners
Experteam (TUR)