In 2024, AI wasn’t just a hot topic—it became a transformation imperative. At Celosphere ‘24, Celonis showcased how Process Intelligence is the critical foundation for enabling AI in the enterprise. AI alone isn’t enough—it needs business context, and that’s where Celonis delivers. From enabling AI agents with real-world process insights to turning unstructured data into structured intelligence, Celonis introduced game-changing AI innovations.
First is AgentC, a suite of AI agent tools, integrations, and partnerships that allows our customers to use AI agents pre-built by partners, as well as develop their own in the leading AI platforms. Annotation Builder is a no-code tool that uses GenAI to reason through data, whether structured or unstructured, and generate decisions and action recommendations. And then there are Process Copilots, which enable analysts to interrogate their data using ordinary, non-technical language and receive rapid insights about process improvements.
So what can our customers do with it all? To find out, we held the first in an on-going series of one-day AI Lab events. Customers were invited to get hands-on with our latest AI innovations to discover and build impactful solution prototypes. Here’s a round-up of what they built.
We hosted five AI Lab events in 2024 across four cities Munich, Madrid, London, New York, and at Celosphere itself. These events involved over 100 participants, dozens of customers and multiple partners, who built AI solutions for some of their most pressing business challenges.
The AI Labs weren’t just about technology—they were about collaboration, competition, and co-innovation. The teams competed to create the most impressive functional prototypes, leveraging Celonis process insights and AI capabilities, including Process Copilots, Annotation Builder, and the ML Workbench – in just one day. These solutions were pitched to fellow participants and Celonis AI experts, charged with the unenviable task of selecting the winners, an esteemed jury of Celonis Product and Engineering leaders.
Participants described the experience as highly hands-on, with one noting, “The AI Lab was very hands-on, and it was great to see the results from all the other teams to get inspired by the wide variety of use cases we can deploy with Celonis AI capabilities.”
The competitive framework fostered innovation, with one participant noted the “excellent Celonis support throughout the preparation and implementation of use cases; inspiring presentations; great discussions with the Celonis team.” And another saying, “Great collaboration and use case exploration.”
Another attendee highlighted the energy and teamwork, saying, “Good energy, great people, and valuable learnings.” Across industries, from finance to manufacturing to logistics, customers walked away not just with solutions but with a clear roadmap for integrating AI into their operations—reinforcing the belief that “Celonis AI Labs showcase why there’s no AI without PI.”
Let’s take a look at the innovations our customers achieved with Celonis’s AI solutions, which made picking just one winner at each event so difficult.
The use cases spanned broad business processes such as Order Management and Accounts Payable, as well as industry-specific processes such as baggage handling. They formed inspiring snapshots of how customers can use Celonis to create custom solutions with chatbots and agents that realize tangible benefits fast.
At the end of each exciting day of tireless solution development, teams had ten minutes to present their project. They discussed the business problem they set out to solve, and how impactful the full solution would be, as well as how creative they were in using AI to its fullest capabilities. Finally, they covered the technical execution, including how accurate each solution was and how easy it would be to scale.
Here’s a look at the winners at each 2024 AI Labs event.
Process: Manufacturing
Capability: ML Workbench + Process Copilot
Use case: The manufacturer’s solution enables quicker and more informed decision-making on the shop floor. Historically, root cause analysis of process issues and corrective actions were stored in inaccessible, unstructured PDF data silos. The team showed how these could be organized into one consistent, accessible knowledge base (including data on past problems). The new approach would allow the company to identify patterns, and match past resolutions to new defects in real time. Ultimately, improving product quality, customer satisfaction, and agility.
Process: Incident Management
Capability: ML Workbench
Use case: Streamlines triaging of incidents, which significantly impact delays; saves costs by reducing operator penalties and ticket refunds, while improving customer satisfaction by minimizing service delays; Instead of manual review and retrospective data entry into systems of record, incoming calls are converted into structured text, categorized, and matched to past incidents to recommend the top three most similar cases for quicker resolution.
Process: Procurement & Inventory Management
Capability: Annotation Builder + Process Copilot
Use Case: Enhances decision-making by contextualizing safety stock recommendations, categorizing updates, and identifying on-time-in-full (OTIF) root causes; recommendations are bucketed into clear categories and pushed back to material planners for review and decision
Process: Procurement
Capability: Annotation Builder + Process Copilot
Use Case: Maximizes contract usage by classifying generic materials and suggesting suitable alternatives; gives non-technical users the ability to quickly query and analyze procurement workflows, delivering actionable insights, like identifying contracts that need attachment
In addition to the winners, here are some of the outstanding solutions that were developed during the AI Labs.
Process: Accounts Payable
Capability: Action Flows
Use case: Automates time-consuming manual maintenance of Purchase Order data that causes long lead times between PO placement and delivery; automatically reads unstructured emails to identify PO confirmations and update the corresponding PO in the SAP system
Process: Order Management
Capability: Annotation Builder + Process Copilot
Use case: Optimizes working capital by increasing Revenue Realization from faster invoicing, and improves customer satisfaction through increased on-time deliveries; accelerates customer deliveries by deploying a Credit Block Assistant that recommends the next best action for active credit blocks
Process: Baggage Handling
Capability: Annotation Builder + Process Copilot
Use case: Addresses costly high volumes of mishandled baggage by understanding the root causes behind left-behinds, and identifying specific flights to prioritize; reviews metadata, inbound and outbound flight data, and actual transfer times to automatically recommend the correct reason for loss code
Process: Opportunity Management
Capability: Annotation Builder
Use case: Boost deal closure rates by understanding and automatically prioritizing which customers are ready for an upsell based on sentiment analysis of previous communications and account team notes
Process: Customer Service
Capability: ML Workbench & AI Annotation Builder
Use case: Uses AI-based pattern recognition to identify key drivers of multiple customer contacts and predict occurrences, enabling proactive communication and case prioritization; saves costs through reduced number of customer contacts, while improving customer satisfaction
Process: Accounts Payable
Capability: Process Copilot
Use case: Simplifies the complexity and resources required by invoice status requests through natural language queries, reducing the time required to handle each invoice
Process: Production
Capability: Process Copilot
Use case: Identify expired or soon-to-expire base modules in high-voltage storage production, reducing waste and accelerating module reuse
Process: Material Goods Movements
Capability: Annotation Builder + Process Copilot
Use case: Detect and flag suspicious transactions and material movement, reducing fraud and manual efforts while preventing potential losses from write-offs
We’re just getting started – look out for the 2025 AI Labs calendar. We’re planning 20 events between February and July. That means more cities, more customers, more innovation – and more AI.