Jira Service Management

Project Description: Implementation of a Service Desk Based on Jira Service Management

1. Project Name

Implementation of a customer support service desk system based on Jira Service Management

2. Project Goal

Creating a unified automated system for handling customer requests with SLA support, integration with a knowledge base, Crisp chat service, external APIs, and internal responsibility distribution across support lines.

3. Objectives

• Reduce workload on first-line support.

• Automate processing of repetitive requests.

• Centralize request accounting and SLA control.

• Build a single customer portal.

• Integration with external systems: charging station database, Crisp, Microsoft 365.

• Provide service for both private and corporate clients.

• Launch a knowledge base with automatic recommendations.

• Develop a reporting system: response time, operator workload, etc.

4. Key Project Components

• Jira Service Management Cloud — as the main platform.

• Confluence — as the knowledge base (internal and public).

• Crisp.chat — as an omnichannel chat provider.

• Microsoft Entra ID — user authorization.

• External API Integration — for charging stations, ports, etc.

5. Support Portal Functionality

Users will be able to submit requests by categories:

• Station issue

• Mobile app error

• Payment issues

• Other questions

Custom fields (dynamic, with API) will be automatically pulled for better processing (e.g., station, port, error code, LOG, etc.).

6. Support and Escalation

• First line — operators.

• Second line — service team.

• Third line — engineering team.

• Ticket routing between lines.

• SLA policies for different client types.

7. Integrations

• Crisp.chat → Jira — creating tickets from chat.

• Confluence — automatic article suggestions from the knowledge base.

• API for charging stations — dynamic form filling.

• Microsoft 365 SSO — unified user authorization.

8. Automation

• Chatbot for answering common queries.

• Automatic identification of corporate clients.

• Automatic request escalation.

• SLA reminders and notifications.

9. Analytics

• Queue formation.

• Reports on SLA, priorities, operator productivity.

• Support line workload.

10. Expected Results

• Up to 50% reduction in operator workload.

• Improved response times (SLA).

• Single point of contact for all requests.

• Increased customer satisfaction.

• Clear responsibility structure.