Celonis Product Documentation

You can now establish zero-copy connectivity between your Microsoft Fabric enterprise data lake and the Celonis Platform, allowing you to share data between the platforms with zero latency. This means that any updates in your data lake are automatically shared to your Celonis data pool.

The benefits of this connection include:

To learn more about connecting to your Microsoft Fabric account, see: Microsoft Fabric.

And for a video demo:

Process Adherence Manager now supports dynamically-generated or relabelled events, allowing you to specify the granularity of your process by adding attributes to existing event types. This means you don't need to know all the event types you'll need when you start creating your model; instead you can simply and flexibly add them as required.

You can define dynamically-generated or relabelled events in the following ways:

You can also rename dynamically-generated or relabelled events in the PQL Editor.

We’ve also added support for case-centric data models, meaning Process Adherence Manager now works for both object-centric and case-centric data models.

To support these enhancements, provide better alignment with Studio and give a more consistent experience across the Celonis Platform, we've also made the following changes:

Any filters you set in a View can now also be copied into other Views within your Celonis Platform team, saving you from manually configuring them each time. Copied filters are saved on a clipboard for 10 minutes, with a prompt for you to apply the filter when you open subsequent Views.

To learn more about copying filters between Studio Views, see: Copying filters between Views.

The Python tool in Process Copilots is designed to allow ad-hoc Python code executions. With this launch, we’re releasing a visual editor for the Python tool and allowing users to customize the tool. This editor can be added to the configuration settings of a Process Copilot as a tool to utilize both of these configuration methods.

In the Intelligent Configuration, the Large Language Model (LLM) generates Python code based on the questions users ask to this Process Copilot. For Process Copilots utilizing the Intelligent Configuration, the Python code is generated ad-hoc as questions are asked. In the Intelligent Configuration, to run Python code, the LLM needs a dataset on which to run the code. To provide the Python tool with an available dataset, you need to have at least one data retrieval tool activated (get_data, pql_tool, get_process_data - depending on the use case).

In the Custom Configuration you can manually define the dataset to run the Python code on. Users can then enter their Python code in an editable interface which will work dynamically to expand the code as it is written. This interface also allows users to define which inputs can be used as variables or parameters by end users when asking questions in the chat. Users can also use the built-in code assistant to create their Python code using natural language commands to describe the use for this code.

For more information, see Tool Activation.

We’ve added Celonis IP as origin addresses for eu-2, jp-1, uk-1 and us-2. If you have IP allowlisting configured for Celonis-originating traffic, you must add the following IP addresses to avoid connectivity issues with cloud databases and/or on-premises services:

For:

We've made a number of enhancements to our Objects & Events transformations, including the following:

For more information about modeling your objects and events, see: Creating custom transformations.

You can now run multiple object-centric data jobs in parallel for different perspectives. If there are overlaps in your required objects or events, the respective transformation will be queued to avoid read-write conflicts.

In this example, a 'Sales Order' object is being used in both the Accounts Receivable (AR) and Order Management (OM) processes. These data jobs are scheduled to run at the same time:

When you check the transformation logs, you can then seen that the OM task is queued while the AR task runs. Once the AR task has finished running, the OM automatically executes:

For more information, see: Creating custom transformations.

A new feature has been added to both Process Explorer and Variant Explorer which enables analysts to create groups of custom process KPIs that can be displayed in the process graph. Analyst users can create a KPI Group by selecting existing process-related KPIs or defining their own KPIs using the visual editor. The analyst can then share these KPI Groups with their end users who will be able to display these KPI Groups in the process graph of their Process Explorer or Variant Explorer. KPI Groups can be created for both case-centric (single event log, multi-event log) and object-centric process exploration components.

The new built-in visual editor allows users to create KPIs without advanced YAML skills and speeds up the creation process for new KPIs. Users are able to define KPIs directly in Studio without having to switch to the Knowledge Model or perform manual coding.

Both KPI Groups and the individual KPIs within those groups are created and stored in a Knowledge Model. As a result, if a change is made to an individual KPI, that change is automatically updated in any KPI Groups to which that KPI was added.

For more information see Custom KPI Groups in Process Explorer and Custom KPI Groups in Variant Explorer.

The AI Settings page in Admin & Settings is being updated to include a new option for Large Language Model (LLM) deployments and provide Admins more insight into the AI assets being used by their team. These new features will provide Admins with an additional option for their AI services, as well as providing both more insight into where their assets are being used and more control over the AI Output consumption.

Admins will be able to configure the Bring your own Model (BYOM) option to connect self-hosted LLMs on Azure, AWS and OpenAI compliant environments to their Celonis teams. This feature allows Admins to reuse their existing LLM deployments in Celonis.

Users can also see the specifics of their AI consumption in the Consumption Details screen by clicking the “See consumption details” in the upper right of the AI Settings screen. From this screen, users can see the total number of outputs being consumed by each Service Provider, as well as a more detailed breakdown of each AI product in the Consumers table, including the assigned LLM, when the product was last used, and the number of outputs consumed.

The new AI Assets in Studio tab provides a detailed breakdown of the team’s AI Assets, such as Annotation Builders and Process Copilots, that are currently in use. From this tab, Admins can see where each AI asset is being used, the type of asset, the LLM assigned, and the service provider. Admins can also use the toggle switch to disable individual assets and pause their AI Output consumption.

For more information, see AI Settings.

Process Explorer is adding a menu for users to control the list of events and activities displayed in their process graph by hiding any specified activities that the user is not currently interested in. For example, users can hide an activity that occurs in all cases or activities that are generated automatically as part of the workflow. By hiding these activities, the user can focus on the activities they are most interested in.

The menu is displayed in the upper right of the Process Explorer and shows both the total number of activities and the number of activities currently selected, such as 17 of 21 events in the multi-object screenshot below. After clicking to expand the menu, users can select the check boxes to indicate which activities to include in the process graph. Removing the check mark will cause an activity to be hidden.

Activities menu - case centric	Events menu - multi-object

Once all activities have been selected, click Update to apply the changes and refresh the process graph. The totals and KPIs on the process graph are updated based on the selected activities. The global sliders are also updated to reflect the total number of available activities based on the menu selections.

For more information, see Show / Hide events.

We've made two enhancements to our Objects & Events product area:

For more information about modelling your objects and events, see: Modeling objects and events.

With this release, we've added five new project plans to our Celonis for Consulting product area. These new project plans are:

We've also significantly upgraded our existing project plans (Discover, Execute, and Operate), introducing new features and enhanced capabilities.

For an overview of these plans, head to: Celonis for Consulting.

We've updated the CPM login page to use Celonis branding and logos. All other functionality remains the same.

For more information, refer to the documentation.