Celonis acquires Ikigai Labs to boost enterprise AI context
Celonis has acquired Ikigai Labs to add decision-intelligence technology to its process-mining platform. The company says the deal will help power a new Context Model meant to give enterprise AI a real-time view of how businesses operate.
Celonis SE has acquired decision-intelligence startup Ikigai Labs Inc. and plans to use its technology to support a new Context Model for enterprise AI, the company said today. Celonis says the model is designed to act as a real-time digital twin of a customer’s operations, giving AI systems the business context they need to make better decisions.
The acquisition brings together Celonis’ process intelligence platform and Ikigai’s structured-data modeling technology. Celonis Chief Product Officer Dan Brown said in a blog post that AI models often do not understand how key business records relate to each other because the data is private, proprietary and scattered across different systems. Without that operational foundation, he said, AI agents cannot be trusted to make reliable real-time decisions.
Celonis said the Context Model is intended to remove those blind spots by turning business processes into a language AI can understand. The company described it as a “dynamic, real-time digital twin of operations” built from process data and business knowledge gathered across applications, systems, devices and interactions inside an organization. Celonis said the result is meant to provide the operational clarity AI needs to reason correctly.
The company said it had been working on the Context Model for more than two years. Celonis President Carsten Thoma said in an interview with Computer Weekly that the goal was to build a “holistic business graph” that could serve as the brain of a company’s AI operations. He said enterprise application landscapes are fragmented, data lakes compete with each other and many AI use cases are hard to deploy efficiently.
Thoma said Celonis already had part of the answer in its process intelligence platform, but was missing the “large graphical model” that Ikigai provides. “AI is only as good as the context it has,” he said, adding that every organization needs a living model of how the business truly operates.
Ikigai was founded in 2019 and is led by Chief Executive and Chief Technology Officer Devavrat Shah, who also holds a professorial chair in AI at MIT. The company focuses on structured data and sells a generative AI platform based on “large graphical models” that help AI systems understand proprietary enterprise data.
Shah, who is now chief scientist for enterprise AI at Celonis, said Ikigai’s technology and Celonis’ process encoding together provide a fuller operational picture of business reality. He said enterprise AI needs to understand the peculiarities of structured business data at scale.
Celonis also pointed to early adopters of the Context Model, including Cardinal Health LLC. The healthcare services company’s CTO, Jerome Revish, said his industry cannot accept AI systems that are “only right most of the time.” He said precision matters, and that process context and guardrails help teams use AI with confidence.
The platform includes zero-copy integrations with Amazon Web Services, Databricks and Microsoft Fabric, along with connectors to Oracle’s database and other enterprise systems. Celonis also said it integrates with agentic development platforms including Amazon Bedrock, Anthropic’s Claude, IBM Watsonx Orchestrate, Microsoft Copilot and Agent365, and Oracle Cloud Infrastructure Enterprise AI.
Celonis competes in business process mining and process intelligence with SAP’s Signavio, IBM Process Mining and UiPath. Investor Ashu Garg of Foundation Capital, an early backer of Ikigai, said Celonis now has a stronger context-graph approach after adding Ikigai’s decision-intelligence and simulation capabilities.
