Solution

AI Service Desk Copilot

An AI layer for Service Desk that reduces the load of the first line, speeds up the classification of requests, prompts the operator for the next step and turns the knowledge base into a working support tool.

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Product positioning

AI Service Desk Copilot does not replace an ITSM system. It becomes an intellectual layer on top of requests, knowledge base, regulations and decision history. The product helps you quickly understand what happened, who to assign a task to, what response to prepare, and what knowledge base articles to use.

Such a module is especially valuable in large organizations, where support processes thousands of standard and atypical requests, and the quality of service depends on the speed of classification, completeness of context and compliance with SLAs.

Benefits for the client

Load reduction L1

Typical requests are classified faster, receive a draft response, and require less manual searching.

SLA acceleration

The operator quickly understands the priority, category, similar incidents and possible solution.

Consistent response quality

The answers are based on the knowledge base and regulations, and not just on the experience of a particular specialist.

Development of the knowledge base

Recurring requests are turned into articles, tips, and improvements to the support process.

What the module can do

Intake

Reception and classification

Recognizes the request subject, category, priority, possible route and missing data.

Assist

Operator Tips

Generates a draft response, suggests diagnostic steps, searches for similar incidents and relevant articles.

Knowledge

Support knowledge base

Uses RAG for regulations, instructions, FAQ, request history and internal documents.

Control

SLA and quality

Helps monitor statuses, escalations, problem recurrence, activity log and response quality.

Integrations

environmentWhat do we connect?
ITSM and task trackingJira, Naumen, ServiceNow, 1C ITIL, internal Service Desk and ticket systems.
Request channelsCorporate portal, web interface, mail, Telegram/Web, internal bots.
Knowledge BaseConfluence, regulations, support instructions, FAQ, internal portals and file storage.
ReportingSLA metrics, categories, reasons for requests, repeatable problems and quality of processing.

How we implement it

Step 1

Discovery

We fix the business process, data sources, user roles, information security restrictions, benefit criteria and the first scenario.

Step 2

MVP

We launch the working module in a limited loop, connect data, roles, logs, interface and quality control.

Step 3

Pilot

We test the effect on real users, set up rules, finalize integrations and prepare for operation.

Step 4

Scale

We expand the module to new units, sources, roles and scenarios without breaking the platform core.

Enterprise control

Data under control

Sources, permissions, logs, and restrictions are fixed at the architecture level rather than added after launch.

Integrations

Modules connect to ERP, 1C, SAP, DWH, EDMS, Service Desk, GitLab, Jira, Confluence, portals and internal APIs.

Verifiability

Answers and actions should be explainable: sources, versions, logs, processing statuses and the responsible owner of the process.

Scaling

Each of the following scenarios uses the platform core: roles, models, RAGs, logs, connectors, and security rules.

Infrastructure for AI Service Desk

Service Desk AI works with requests, SLA, knowledge base and decision history, so it needs a reliable environment: production API, logging, task queues, monitoring, backup and secure access to sources.

Frequently asked questions

Is it necessary to change the existing ITSM?

No. Typically the module is built on top of the current ticket system and knowledge base.

Does AI close requests itself?

In critical processes, AI prepares hints and drafts, and the decision is made by the operator or process owner.

Can it be used for HR and financial support?

Yes. The logic is suitable for any internal services that have requests, regulations, a knowledge base and SLA.

Enterprise product packaging

AI Service Desk Copilot is delivered as a module of the RESTART AI Enterprise Platform: with a clear area of ​​responsibility, business process owner, data model, integrations, roles, logs, pilot criteria and production plan. This is important for CIOs and CISOs: the module does not live separately from the corporate architecture, but is integrated into the IT landscape, security, operations and change management.

Business effect

Success criteria are formulated before the pilot: time, quality, reduction of manual workload, speed of response, completeness of data or controllability of the process.

Integrations

The module connects to customer systems: ERP, 1C, SAP, BI, DWH, EDMS, Service Desk, Git, portal, mail, documents and internal APIs.

Information security and compliance

The separation of roles, sources, loops, logs, and data is considered at the architectural level rather than added after launch.

Scaling

After the first successful scenario, the module can be expanded to new departments, documents, processes, users and regions.

How to show value per pilot

1

Select one process

Don’t try to automate everything at once: choose a process with an understandable pain, an owner and a measurable result.

2

Connect data

Collect a limited but real set of documents, applications, reports, code, regulations or historical requests.

3

Check with users

Conduct a pilot on working scenarios, collect feedback, adjust the quality of answers and control of controversial cases.

4

Design an production environment

Fix the architecture, roles, regulations, SLA, monitoring, support and development roadmap.

Let's discuss your environment

Describe the task, current systems, constraints, and expected results. We will offer a practical first step: diagnostics, pilot, audit, roadmap or project team.

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