27.08.26 (inclusive)

Contractual

Idea

ICT tasks

Car industry

Neurotechnology and artificial Intelligence

Software/ IS

Currently, the primary classification, tagging, and distribution of incoming tickets in TechDrive's Service Desk are performed entirely manually by first-line support staff. This entails a number of critical problems.: High first reaction time (SLA) for task allocation during peak load periods. Periodic errors of the human factor during routing (incorrectly defined category sends a task to the wrong team, increasing the total solution time). Distortion of the accuracy of analytical data due to incorrectly manually assigned tags, which prevents management from identifying real bottlenecks in products.

Reducing the first reaction time (SLA): Eliminating manual processing at the initial sorting stage will allow incoming requests to be distributed instantly (within a few seconds after they are created). Increased routing accuracy up to 95%+: Automation based on a trained AI model minimizes the "human factor" and eliminates situations where an application is mistakenly sent to the wrong team of specialists. This will shorten the overall incident resolution cycle. Optimizing resources (Unloading the first line): Freeing technical support staff from the routine sorting of tickets will allow them to redirect their resources to solving complex technical problems and high-quality processing of atypical requests that require manual moderation. Absolute purity of analytical data: Error-free automatic tagging and categorization of incidents will provide TechDrive management with 100% reliable statistics on product bottlenecks for strategic decision-making.

Tankayeva Jamilia