Celonis launches Solution Suites and enhances AgentC, advancing its 'No AI without PI' strategy for faster enterprise adoption

Process mining vendor Celonis has made a series of significant platform announcements at its Celonis:Next 2025 event this week, including the launch of new Solution Suites and updates to its AgentC AI capabilities. The company continues to push its "No AI without PI" messaging, arguing that enterprise AI needs process context to be effective.

These announcements come just seven months after Celonis first introduced AgentC at its Celosphere event in Munich last October, as the company continues to position itself in the enterprise AI conversation.

Alexander Rinke, Co-CEO and co-founder of Celonis, used his keynote this week to emphasize how AI requires business context:

I don't need to tell you that there's a lot going on in the world right now, and change is happening faster than it ever has. But what has not changed is our mission at Celonis to make processes work for people, for companies and for the planet. That means driving real results, creating real, tangible value.

Rinke argued that generic AI tools have limitations in business settings, explaining:

AI is great for everyday tasks, but it's also only scratching the surface of what's really possible. What if you could ask an AI agent which customers' deliveries are at risk, and then have it take automated action to reroute deliveries and notify logistics partners. That's an AI that doesn't just write an email for you, it helps you mitigate supply chain disruption.

The Process Intelligence Graph expands

Central to Celonis' strategy is its Process Intelligence Graph, which the company describes as a "living digital twin" of business operations. This approach builds on the company's earlier shift from traditional case-centric process mining to object-centric process mining.

This evolution is significant because, as Professor Wil van der Aalst, Celonis' Chief Scientist, previously explained, traditional process mining follows a single object (such as an order) through an organization but struggles to account for how multiple objects interact. Object-centric process mining allows organizations to map beyond single processes and understand how they interact, creating what Van der Aalst called a more "three dimensional" view.

The distinction matters particularly for AI applications. When AI can only access isolated process data, its recommendations remain similarly isolated and often miss critical dependencies between processes. For instance, an AI agent focused solely on order management might recommend actions that optimize that specific process but create bottlenecks in production or shipping.

As Van der Aalst explained in an earlier interview: 

If you look at one object, you will not see, for example, when you're handling a sales order, how that is being delayed by things in production. Using object centric process mining, you bring this together in a very flexible way, and you can basically choose your angle that clearly shows you in the sales process how we have this problem - but it's not caused by the sales department, it's actually the production department.

This enterprise-wide process understanding is what enables AI agents to make recommendations that account for cross-process impacts and dependencies. Without this broader context, AI would essentially operate in the same siloed manner that has limited traditional business applications.

This context frames the announcements made by Celonis this week. Paul Dickinson provided more details during the event: 

The Process Intelligence Graph is at the heart of the Celonis platform. It's the living digital twin of your enterprise that brings together process data and business context. It spans multiple systems and captures contexts like KPIs, industry benchmarks, process models and so much more, and provides a common language for all of them.

The latest PI Graph updates include an expanded pre-built objects and events catalog for various systems, including "Salesforce, Microsoft Dynamics 365, Zendesk, Oracle Fusion, S/4 HANA, Workday, ServiceNow, and even supply chain specific systems like Blue Yonder. 

For existing customers who have been using case-centric data models, Celonis has created migration paths. Dickinson noted that the company has made it easier to "bring your existing data models into the graph without starting from scratch. Long time Celonis customers will be able to leverage your existing case centric data models to get a head start on the PI Graph."

The company has also added new version control features that allow teams to track changes, undo production changes, and improve collaboration.

AgentC updates and Orchestration Engine

After introducing AgentC at Celosphere in October 2024, Celonis has now expanded its capabilities with an extended Process Intelligence API for sharing PI context with AI platforms like Microsoft Copilot Studio, Amazon Bedrock, and Salesforce Agentforce.

The company previously acquired Orchestration Engine from its partner Emporix. This tool aims to connect and coordinate tasks across different systems and departments, using real-time Process Intelligence data to monitor workflows and direct processes.

Additionally, Celonis announced that its Process Copilots are now generally available in collaboration tools like Slack and Microsoft Teams, and the Annotation Builder, for recommending decisions, has also reached general availability.

Brian Dodson, Business Process Improvement Manager at Smurfit Westrock, described how his organization is using these capabilities: 

Our plant technicians can now ask their Process Copilot to locate and arrange transfers of spare parts from other plants, minimizing disruption and maximizing value by keeping our operations running smoothly.

Solution Suites - Packaging expertise

Perhaps the most notable announcement was the introduction of Celonis Solution Suites – packages that combine connectors, pre-defined process data, business context, and pre-built apps. Four suites are available at launch:

• Supply Chain Solution Suite
• Finance Solution Suite
• Front Office Solution Suite
• Sustainability Solution Suite

Dan Brown, Chief Product Officer at Celonis, explained the thinking behind Solution Suites: 

How do you bring everything you've seen here today to your specific department fast? While we've invested in making the platform easier and faster than ever to use, we know starting from scratch still takes work, building the data models, defining the knowledge and creating the apps to accelerate your journey.

The aim is clearly to address one of process mining's persistent challenges: scaling from isolated use cases to enterprise-wide adoption. Jan Philipp Thomsen, VP Product Management, emphasized that the Solution Suites are based on "a decade of experience from thousands of deployments. Having all of this pre-built dramatically speeds up the time your center of excellence is spending to deploy and roll out Celonis."

Thomsen provided an example of the Supply Chain Solution Suite in action, describing how a customer service representative handling a complaint about a delayed order could use the tool inside Salesforce’s Agentforce: 

The rep starts the day in Salesforce CRM, answering customer tickets with the help of an Agentforce AI agent. Now this ticket is from a priority customer who's complaining that a critical order has been delayed. And so to understand why the order is delayed, he usually spent a lot of time consulting emails, spreadsheets and ERP modules, but thanks to Celonis, Agentforce understands what occurred in the supply chain that led to the order being delayed, and so the agent can rationalize the best action to take by considering the full picture. 

So we can see that this order was delayed because of a credit block, and Agent Force recommends that the credit management team review to see if the block can be removed, and that the logistics team can expedite the order, so now we know exactly what the problem is, and we've sent our agent to reach out to the right teams in a fraction of the time it usually takes.

Platform improvements focus on usability

Alongside these announcements, Celonis introduced several other platform improvements:

• A new Process Query Language (PQL) Editor that connects to customer Knowledge Models
• Microsoft Fabric integration, making Celonis Process Intelligence available as a workload in Microsoft Fabric
• A Process Management API integration for uniting process mining and modeling
• An event log builder for on-the-fly event log creation and exploration
• More customizable Studio Views with scalable View Modules

Brown summarized these changes, saying: 

With AgentC and our Process Intelligence API, we're helping customers maximize the ROI of their AI deployments. Orchestration Engine enables stronger oversight and control of process workflows. And Solution Suites shorten time to value by making it faster and easier to deploy PI and AI across the enterprise.

Building on past strategy shifts

These announcements continue Celonis' evolution from a pure process mining company to one focused on broader process intelligence. This journey began with the company's shift to object-centric process mining, creating what Juergen Kuebler, VP of Industry Value Engineering at Celonis, previously called a ‘semantic layer’. Kuebler recently told diginomica: 

What [other platforms] don't have is this additional semantic layer. And that's a critical difference. The Process Intelligence Graph describes to people in terms that you and I understand... And when you start building software on top of that layer, it's so much easier. 

Earlier this year, Celonis began expanding this platform approach by launching partner apps for specific use cases like insurance claims processing and sustainability. The introduction of Solution Suites appears to be the next step in this strategy, making it easier for customers to adopt process intelligence across different departments.

Celonis' announcements this week reflect a growing recognition in the industry that enterprise AI requires business context to be effective. As my colleague Phil Wainewright recently explained, AI systems struggle to interpret data reliably without a frame of reference.

This was demonstrated by Rinke at the Celosphere event last October, when he showed ChatGPT attempting to answer a nonsensical question about "excess stock levels and safety stock levels in HR." Despite combining inventory concepts with human resources – a meaningless combination – ChatGPT produced an elaborate response filled with HR buzzwords.

This illustrates a fundamental challenge for AI in enterprise settings: without understanding business operations, AI tools may produce plausible-sounding but ultimately unhelpful responses.

The Process Intelligence Graph aims to address this by providing AI with operational context. As Dan Brown noted in a recent interview, having an intelligence graph helps organizations understand "how things work," enabling them to "indicate, from an orchestration and an agentic AI perspective, what to go and do."

Brown also highlighted the importance of creating a complete feedback loop for AI systems – an element that's often missing in enterprise AI implementations.

My Take

With its latest announcements, Celonis is addressing a fundamental challenge: making process intelligence more accessible and easier to implement. Process mining has always offered valuable insights, but scaling these insights across an organization has sometimes proven difficult. The Solution Suites approach is a pragmatic response to this problem, packaging everything needed for specific departments to get started quickly.

What's interesting is how Celonis is positioning these developments within the context of enterprise AI. While many vendors are simply adding AI features to existing products, Celonis is developing a more coherent narrative about why process intelligence matters for AI effectiveness. The argument that AI needs business context to deliver useful results speaks directly to the challenge of enterprise-wide AI use, especially as organizations start to realize that generic AI tools often produce underwhelming outcomes in complex business settings.

The expanded use of Orchestration Engine, thanks to the Emporix acquisition, is also noteworthy. It suggests Celonis understands that analyzing processes isn't enough – organizations also need tools to actively manage them. This moves Celonis beyond analytics into the realm of operational control, potentially making it more central to day-to-day business operations.

As organizations become more discerning about their AI investments, thanks to often underwhelming results so far, Celonis' focus on operational context and tangible outcomes could prove valuable. But the company will need to continue showing that its process intelligence approach delivers transformative results rather than just interesting insights. The next year will be crucial as customers begin implementing these new capabilities and we see whether the Solution Suites truly accelerate time-to-value as promised.