Overview

Starting with Version 2026.1, AI is now a native, provider-agnostic capability of the ESM Platform. 

Customers can design, configure, and execute AI-powered functions using a low-code approach, embedding AI directly into existing workflows, UI actions, and the M42 Assist experience. AI is therefore available as an integrated platform capability rather than as a separate application or isolated feature.

This approach:

• Enables AI extensibility through low-code configuration. 
• Embeds AI directly into existing business processes and user interfaces. 
• Supports different AI providers through a standardized integration model. 
• Reduces dependency on a single AI vendor. 
• Simplifies the adoption, deployment, and scaling of AI use cases. 
• Preserves the existing Matrix42 security and action model.

A centrally configured AI provider framework currently supports: 

• Matrix42 Intelligence
• OpenAI
• OpenAI-compatible providers 

The provider can be changed without redesigning the AI Function or the business process that uses it. 

AI Function executions are recorded with relevant execution information, such as the selected function, provider, request, response, and execution status. This supports troubleshooting, auditability, and controlled use of AI capabilities.

Terminology Update: Neo

The agentic AI and LLM features described in this article, previously branded M42 Intelligence, are consistently renamed Neo across the ESM platform, including an updated logo and color scheme.

This includes the M42 Assist, or AI Assist Bar name as Ask Neo, and AI-related ticket journal entries, which now name the agent explicitly, for example "Ticket Automatically Resolved by Neo" instead of generic "AI" wording.

Requirements

During Preview, customers must have one of the following subscriptions: 

• ITSM 2023 Advanced or Enterprise
• ITSM 2025 Enterprise
• A later supported subscription

When Matrix42 Intelligence is configured as the AI Service Provider, an active Matrix42 Intelligence subscription and sufficient Action Credits are also required. When customers use their own supported AI provider through Bring Your Own Model (BYOM), they are responsible for any consumption, licensing, or infrastructure costs charged by that provider.

Availability by Deployment Model

Predefined AI Functions

Matrix42 provides a predefined set of AI Functions that can be used immediately after a supported AI Service Provider has been configured.

The predefined functions include: 

Detect Ticket Category 

Analyzes the ticket content and suggests the most appropriate service category. 

The suggestion is based on the available ticket information, including fields such as the title and description. 

Detect Ticket Impact

Analyzes the ticket context and suggests an appropriate impact value. 

The result can be reviewed by the user before it is applied to the ticket. 

Detect Ticket Service

Identifies the service that is most likely related to the reported issue or request. 

This can help reduce manual classification effort and improve routing and reporting quality. 

Detect Ticket Type 

Determines whether the ticket is more likely to represent an Incident, Service Request, or another supported ticket type. 

Detect Ticket Urgency

Analyzes the reported situation and proposes an urgency value. 

The function supports consistent ticket assessment while keeping the user in control of the final value. 

Detect Ticket Solution

Analyzes the ticket and available context to suggest a possible resolution.

Depending on the configured scenario, the result can be shown as information, copied into the ticket, or used by an automation process. 

Detect Ticket Solution by Related Items

Similar to the previous AI feature, “Detect Ticket Solution,” this feature analyzes not only the current ticket and available context but also a list of similar tickets and relevant knowledge base articles, if provided, to suggest a possible solution.

Depending on the configured scenario, the result can be displayed as information, copied into the ticket, or used by an automation process. 

Generate Ticket Summary

Generates concise, AI-driven ticket summaries by analyzing the ticket’s title, description, comments, and related context. It extracts the most relevant details - such as the issue type, existing communications, actions taken, affected services, key symptoms, and current status to provide a clear, standardized overview that improves readability, accelerates triage, and supports faster resolution.

The result is displayed in three sections: Overview provides a concise summary of the ticket. Communication shows incoming and outgoing communications for the ticket. Actions Taken focuses on the actions taken on the ticket.

Generate KB Draft

Generates a draft knowledge base (KB) article from ticket information, such as the title, description, and solution. Only closed tickets can be considered during KB draft generation.

Depending on the configured scenario, the result can be shown as information, copied, used by an automation process, or applied to turn support tickets into structured, reusable documentation for your KB.
If applied, a new knowledge base article will be created, with a link to it included in the description of the action result.

Detect Similar Tickets

Analyzes similar tickets and relevant knowledge base articles using AI’s advanced analysis capabilities. It provides an intelligent way to identify and surface related historical incidents, service requests, and self-service resources by analyzing the ticket subject, recognizing patterns, and matching contextual similarities across existing records.

The result returns the top 3 similar tickets and the top 3 relevant knowledge base articles that match the current ticket. This information can help identify related items or be used by an automation process for further activities.

Text Enhancement

 Improves the quality of user-entered text. 

Typical use cases include: 

• Correcting spelling and grammar.
• Improving readability.
• Rephrasing text in a more professional tone.
• Making descriptions clearer and more concise. 

Text Summarisation

This is used for summarizing long texts in HTML literal or Ticket Journal 

Auto Translation 

Translates text into a selected target language. This can be used for ticket descriptions, journal entries, knowledge content, and other supported text fields.

UI AI-powered actions

predefined AI-powered action are described here

Customization with Native AI Functions

see next article for details how Native AI Functions can be used for customization here

Predefined Neo Agents

Read about Neo Agents here

AI Service Providers

An AI Service Provider defines which AI backend is used to execute an AI Function. 

The provider configuration is managed centrally. This allows administrators to configure the connection once and reuse it across multiple AI Functions and business processes. 

Supported provider types include: 

Matrix42 Intelligence 

Matrix42 Intelligence provides the recommended Matrix42-managed AI capabilities and can offer additional services beyond basic prompt execution. The exact available functionality depends on the customer’s subscription and deployed Matrix42 services. 

OpenAI 

The platform includes an out-of-the-box integration for supported OpenAI models. Customers must provide the required credentials and configuration for their OpenAI account. 

OpenAI-compatible 

Providers that expose an OpenAI-compatible interface can also be connected. Compatibility depends on the provider’s API implementation and the supported model capabilities.

Configure an AI Service Provider

Before AI Functions can be executed, at least one AI Service Provider must be configured and activated. 

The exact configuration fields depend on the selected provider. In general, the administrator must provide: 

• Provider type 
• Service Connection
• Model or deployment name 
• Activation status 
• Capabilities
• Priority

To configure a provider: 

1. Go to Administration > Intelligence > AI Service Providers. 
2. Create a new provider or open an existing provider. 
3. Select the provider type. 
4. Select the required service connection. 
5. Configure the model configuration. 
6. Specify a Capability, e.g., AI Functions.
7. Activate the provider.
8. Save the configuration. 
9. Test the connection, where available. 

After the provider has been configured, it can be assigned to one or more AI Function implementations.

Configure the System Prompt

The system prompt defines the general instructions and behavioral rules applied when AI Functions are executed through the configured AI Service Provider. 

It can be used to establish common requirements such as: 

• Expected response style and tone
• Language behavior
• Formatting conventions
• Security and compliance instructions
• Restrictions on unsupported or unsafe responses
• General rules that should apply across multiple AI Functions 

The system prompt is combined with the function-specific prompt at runtime. The system prompt provides the general execution context, while the AI Function prompt defines the concrete task, such as detecting a ticket category, translating text, or suggesting a resolution. 

To configure the system prompt: 

1. Go to Administration.
2. Open System Settings → Intelligence.
3. Enter or update the AI Function System Prompt. 
4. Save the settings.
5. Test the affected AI Functions. 

Administrators should keep the system prompt generic and reusable. Instructions that are specific to one business use case should be defined in the corresponding AI Function implementation instead. 

Changes to the system prompt may affect all AI Functions. The updated prompt should therefore be tested before being introduced into productive use.

Configure Application-Specific AI Prompt

In addition to the account-wide system prompt described above, an administrator can define a dedicated AI Application Prompt for each Matrix42 Enterprise application. This prompt adds further context, business rules, terminology, and response guidance that applies only when an AI Function is executed from that specific application.

For example, AI Functions executed in the Self Service Portal can be configured to use simple, employee-friendly language and prioritize self-service solutions, while the same AI Functions executed in the Service Desk can use ITSM terminology and provide more detailed recommendations for agents.

Workflow Designer's Execute Native AI Functions action can also select an application context, so an automated workflow benefits from the same application-specific instructions as a manually triggered AI Function.

Configure Text Translate & Enhance

Administration application → Settings → Regional Settings → Auto Translate & Correct section:

• Enable Auto Translate
• Enable Text Enhancement
• Language Engine:
  • M42 Intelligence (default)
  • OpenAI (gpt-3.5-turbo)
  • OpenAI (gpt-4o-mini)
  • OpenAI (gpt-4-turbo)
• Service Connection: a configured service connection that will process the text, e.g. M42 Next for M42 Intelligence Language Engine or Open AI for other Language Engines. See also, Service Connections.

When enabled, the current auto-translation and text enhancements, including configuration details, are shown on the Global System Settings preview page in the Auto Translate & Correct section as follows:   

How AI Functions Work

An AI Function represents a reusable business capability, such as detecting a ticket category or translating text. 

Each AI Function can have one or more implementations. 

At runtime, the platform: 

1. Identifies the AI Function to execute. 
2. Selects the applicable implementation. 
3. Resolves the configured AI Service Provider. 
4. Collects the required input data. 
5. Sends the request to the selected provider. 
6. Receives and processes the response. 
7. Returns the result to the calling UI action, workflow, or automation. 

An AI Function can return: 

• Informational text 
• Formatted HTML 
• A suggested value
• Multiple structured output values
• A reference to a generated object 

Depending on the scenario, the result can be shown to the user for review or processed automatically by a workflow.

Security and Governance

AI Functions use the existing Matrix42 security and object-access model. 

Access can be controlled through: 

• Roles
• Permissions
• Audience
• UI Action security
• Object-level access

Administrators should ensure that only authorized users can: 

• Configure AI Service Providers. 
• View or change credentials. 
• Create or edit AI Functions. 
• Access execution details. 
• Execute functions against sensitive data. 
• Enable automated AI processing. 

The data sent to an AI provider depends on the configured prompt, input parameters, and object context. 

Administrators must therefore review each implementation to ensure that: 

• Only the required data is sent. 
• Personal or confidential information is handled appropriately. 
• The selected provider meets organizational and regulatory requirements. 
• Data retention and processing conditions are understood. 
• The configuration complies with internal security policies.

Execution Transparency

Each AI Function execution creates an execution record. 

Depending on the provider and implementation, the execution information can include: 

• AI Function
• Implementation
• AI Service Provider
• Execution time
• Execution status
• Input parameters
• Prompt or request
• Response
• Output parameters
• Error information
• Related business object
• Initiating user or process

This information supports: 

• Troubleshooting 
• Prompt optimization
• Auditing 
• Usage analysis
• Provider validation
• Identification of failed executions 

Access to execution details should be restricted because prompts and responses may contain business or personal data

Troubleshooting

AI Function executions can be reviewed from the corresponding AI Function Executions area. 

When an AI Function does not return the expected result, verify the following. 

The AI action is not visible 

Check: 

• Whether the AI Function and UI Action are active. 
• Whether the current object type is supported. 
• Whether the user has the required role and permissions. 
• Whether the UI Action conditions are fulfilled. 
• Whether the required extension is installed. 
• Whether a supported AI Service Provider is configured. 

The action is visible but cannot be executed 

Check: 

• Whether the provider is active.
•  Whether credentials are valid. 
• Whether the configured model or deployment exists.
•  Whether all mandatory inputs are available. 
• Whether the customer has sufficient Action Credits. 
• Whether the provider endpoint is reachable. 

The execution fails 

Open the corresponding AI Function execution and review: 

• Execution status
• Provider response
• Authentication error
• Endpoint error
• Rate limit
• Timeout
• Invalid model configuration
• Invalid prompt
• Missing data binding
• Invalid structured response
• Matrix42 Dispatcher Service not running

For external providers, also review the provider’s own monitoring and consumption portal. 

The result is incomplete or inaccurate 

Review: 

• Prompt wording 
• Data included in the prompt
• Input object quality
• Selected model
• Output format
• Available knowledge or context
• Temperature or provider-specific parameters, where supported 

AI output depends on the supplied context and the selected model. Administrators should test functions with representative customer data before making them broadly available. 

Structured output is not populated 

Check: 

• Whether output parameters are defined in the AI Function. 
• Whether the implementation returns the expected output structure from the Prompt.
• Whether parameter names and types match. 
• Whether the calling UI Action or workflow maps the returned parameters correctly.