Celonis SE is stepping up its efforts to help organizations reshape their business operations with agentic artificial intelligence, announcing today at its annual user conference Celosphere 2025 new capabilities within its namesake Process Intelligence Platform that position it as a foundation for AI-driven operations.

Celonis, which has offices in Munich and New York City, is the creator of a process mining platform that helps companies to identify opportunities to increase their operational efficiency. Its platform can be used to detect if a retailer has more of a certain item than is necessary to meet customer demand, for example, while a shipping company could use it to predict and mitigate delayed deliveries.

The Celonis Process Intelligence Platform works by collecting and analyzing massive amounts of operational data from business applications, devices and systems. It supports more than 1,000 connectors, which reduces the need for teams to create custom code to link those apps to its platform.

Once the data is collected, Celonis enriches it with business context to create a digital twin of an enterprise’s business operations. This is called the Process Intelligence Graph, which enables organizations to analyze, design and operate AI agents and other autonomous processes.

Operational context for AI agents

With today’s update, Celonis is expanding the Process Intelligence Graph to support additional data types from newer data sources. Celonis Data Core is a new offering that enables companies to integrate data lakes such as Databricks and the Azure Data Lake with a simple, zero-copy and bi-directional connection.

The integration with Databricks is significant, because it means live data stored on that platform can be used to create more comprehensive digital twins of business operations. Customers will be able to feed intelligence from the Celonis platform back into Databricks’ Agent Bricks platform and create production-grade AI agents that have been optimized with their own operational data.

To support the creation of more capable AI agents, Celonis has also added new capabilities for connecting desktop actions such as keystrokes, mouse clicks and screen scrolls into business processes that support enhanced task mining and AI-driven task discovery. In addition, enterprises will be able to integrate their architectural blueprints to enable AI agents to understand which systems are used for which activities, so they can use the appropriate tool for each task they’re asked to automate.

All this is being done to support more sophisticated and composable AI-driven operations, Celonis said. To enable these operations, the company has introduced new object-centric process mining tools to help identify problems at key process intersection points, where problems often occur. This will ensure the smooth transition of data across business operations, such as the transport, storage, packing and shipping of final products.

Meanwhile, the company is extending the capabilities of the Celonis Orchestration Engine so it can support AI agents as well as people and systems. It works by converting operational insights into automated task and workflow execution.

Lastly, Celonis said it’s launching the industry’s first Model Context Protocol server designed specifically for process intelligence, which is essential for feeding AI agents with the dynamic operational context they need to make appropriate decisions and complete their work effectively.

Holger Mueller of Constellation Research said process intelligence can be key to ensuring that AI works as intended, which is something that has challenged many enterprises until now. He explained that their reliance on their own data causes all sorts of problems for AI agents especially, because the quality of this information is often questionable, which means their agentic outputs reflect those inaccuracies.

“Celonis provides a promising solution to this by carefully analyzing each organization’s business processes through a loss-free approach that utilizes its latest innovations in object-centric process modelling,” the analyst said. “Its process intelligence graph is a valid and workable alternative to traditional retrieval-augmented generation.”

AI agents in action

In order to showcase what its platform is now capable of, Celonis has worked with several partners to develop a series of “composable” AI agents that can quickly be customized and adopted by customers. These include Rollio Inc.’s new Process Collaboration Agent, which is designed to automate information technology service management, procurement and other common enterprise processes. It’s said to resolve process exceptions instantly by bringing the right people and context from the Celonis platform.

Meanwhile, Trullion Inc.’s new agent helps to automate the complex, manual work needed for lease accounting tasks. Bloomfilter Inc.’s new Agent Miner app is designed to understand and govern the behavior of AI coding agents.

Celonis said a number of early adopters have deployed AI agents that leverage its process intelligence and insights to improve their operations. Mercedes-Benz Group AG has implemented AI agents to accelerate decision making and improve its delivery times, while Vinmar International Ltd. claims to have transformed its cash-to-order process into a fully automated operation.

Celonis Chief Product Officer Daniel Brown said enterprises need to adopt a more structured approach to get agentic AI to work at the level of accuracy and reliability that’s needed. He said this means companies must first identify the right use cases, then redesign their business processes in such a way that facilitates AI automation.

“[The last step is to] orchestrate the agents alongside your people and existing systems,” Brown explained. “Our enhanced capabilities empower customers and their partners to build AI solutions that lift their operations to unprecedented levels of efficiency and agility.”

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