The Context Shift: Celonis & Ikigai Labs Unlock Trusted AI

Enterprises around the world pointing AI and agents at their workflows are running into the same brick wall – does AI understand all of it or are there costly critical blind spots?   

Bridging this gap, Celonis has launched the Celonis Context Model (CCM) – a new layer custom designed to give enterprise AI models a real-time, operational know-how of business processes. 

The process intelligence leader also announced a definitive agreement to acquire Ikigai Labs – an AI-powered decision intelligence specialist bringing advanced forecasting, planning and simulation capabilities into the platform.

“AI is only as good as the context it has,” says Carsten Thoma, Celonis' President.

“Every organisation needs to give its enterprise AI a holistic, living model of how a business truly operates. This has never been possible until now, with the Celonis Context Model.”

Enterprise AI systems lacking necessary operational context required to interpret business processes correctly, according to Celonis, are halting businesses from realising the returns on their aspiring AI investments.

“With Ikigai Labs, we’re making our market-leading platform even stronger: extending its intelligence beyond how your business runs today to how it should – and could – run tomorrow,” Carsten adds. 

Building trusted AI agents with operational context

Celonis Context Model aims at improving the trustworthiness of AI agents in enterprise environments. 

Stemming from the realisation that without a deep domain and decision logic, AI systems risk producing inconsistent or unreliable outputs, Celonis positions operational context as the missing link that will allow smooth transition of AI agents from experimental purgatory to trusted digital workers capable of executing real processes.

The solution CCM turns to is the creation of a dynamic digital twin of enterprise operations. 

This digital twin unifies process data and business knowledge from across systems and interactions, translating it into a structured model that AI agents can use to reason more effectively and act with greater reliability.

By grounding AI within the operational context, AI tools move from isolated insights to coordinated action across the enterprise.

This translates into genuinely useful AI that can be deployed at scale.

The CCM is hence a lifesaver for large organisations with complex global operations, where consistency, governance and precision are essential to ensure safe AI deployment.

Celonis views the Context Model as a foundational layer in the evolving enterprise technology stack – sitting comfortably between raw data systems and AI execution platforms, connecting operational data, business rules and decision logic into a unified structure that AI agents can use.

The Celonis Platform integrates with major ecosystems including AWS, Databricks and Microsoft Fabric, along with enterprise systems such as Oracle and leading CRM platforms. 

It also connects with AI agent frameworks including Amazon Bedrock, IBM watsonx Orchestrate and Microsoft Copilot, ensuring the Context Model is accessible across different environments.

Ikigai Labs brings advanced decision intelligence 

The acquisition of Ikigai Labs well expands Celonis’ AI capabilities as Ikigai’s technology – which is built on nearly two decades of MIT research – specialises in structured data modelling, forecasting and large-scale simulation.

“Ikigai Labs was built on a simple but firm conviction: better enterprise decisions require AI that works with enterprise data,” says Devavrat Shah, Ikigai Labs Co-founder, Chaired Professor of AI at MIT and Chief Scientist of Enterprise AI at Celonis.

“Ikigai Labs has proven foundation model technology for structured data at scale – Celonis has encoded enterprise processes. 

“Together, we provide the fullest operational representation of business reality.” 

Designed to help enterprises shorten planning cycles and predict operational outcomes with higher accuracy, Ikigai’s capabilities when integrated with the CCM, helps organisations move from reactive analysis to proactive decision-making. 

By modelling future scenarios, businesses will be able to anticipate disruptions coming their way and optimise processes before any issues materialise.

With the capabilities rolled into one, Celonis can now support the development of reliable AI agents grounded in both operational history and predictive intelligence. 

This dual capability is central to Celonis’ vision of an AI system that understands not just what is happening in a business, but what is likely to happen next.

“With the Celonis Context Model, AI agents have the hindsight, insight and foresight to intelligently adapt – and can be trusted to deliver the expected business outcomes,” Devavrat says.