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Celonis and deepset launch sovereign AI platform for critical operations. News | June 16, 2026 By Asma Adhimi German software companies Celonis and deepset have teamed up to develop a sovereign AI platform aimed at mission-critical environments, including public sector organizations, defense, cybersecurity, policing, and critical infrastructure. The partnership combines process intelligence with AI agent orchestration to help organizations deploy AI systems while maintaining control over data, models, and infrastructure. For eeNews Europe readers, the announcement highlights the growing push for European-controlled AI technologies at a time when governments and critical infrastructure operators are seeking alternatives to non-European platforms. It also reflects increasing demand for AI systems that can operate in highly regulated and security-sensitive environments. European alternative for sovereign AI. The partnership brings together Celonis' Process Intelligence Platform and its recently introduced Celonis Context Model (CCM) with deepset's Haystack-based AI agent platform. The companies say the integrated platform is designed to provide organizations with a trusted AI environment that can unify operational data, documents, and workflows. The goal is to improve situational awareness, accelerate investigations, identify operational risks earlier, and support decision-making across departments and agencies. A key feature is deployment flexibility. According to the companies, the platform can run on an organization's preferred infrastructure without creating vendor lock-in, allowing users to retain full control over their data and AI operations. "At deepset, we believe organizations need AI systems they can fully trust and control - especially in mission-critical environments," said Milos Rusic, CEO and co-founder of deepset. "By combining Haystack's open and governed AI agents with the Celonis Context Model, we are creating a European alternative for operational AI that is transparent, auditable, and grounded in real-world operational context." Process intelligence meets AI orchestration. The collaboration addresses one of the major challenges facing enterprise AI deployments: providing systems with accurate operational context. Celonis says its Process Intelligence Platform and CCM allow AI systems to understand how organizations function in real time by connecting process data, business knowledge, and decision intelligence. The company argues that this operational layer is often missing from enterprise AI implementations. "AI systems are only as effective as the operational context they are given," said Florian Schewior, Managing Director DACH at Celonis. "By combining Celonis Process Intelligence and Context Model capabilities with deepset's AI orchestration platform, we can help public sector and security organizations deploy AI systems that are not only powerful, but operationally grounded, explainable, and aligned with sovereign infrastructure requirements." Focus on Europe's security and public sector markets. The initial focus of the partnership will be on organizations in the DACH region, while also supporting broader European sovereign AI initiatives linked to security, defense, and public sector modernization programs. The companies said they plan to expand their collaboration through joint customer projects, ecosystem partnerships, and industry events as demand for sovereign AI solutions continues to grow across Europe. Celonis, headquartered in Munich and New York, has built its reputation around process intelligence software, while Berlin-based deepset develops the open-source Haystack framework for building AI applications and agents. Together, they are positioning the new platform as a European-built alternative for organizations that require both advanced AI capabilities and strict control over operational data. Linked Articles

AI Sovereignty: what Breaks When You Build AI. Bilge Yücel from deepset GmbH explains the engineering challenges and solutions for building sovereign AI systems, focusing on data, model, infrastructure, and operational control. In the rapidly evolving AI landscape, the concept of sovereignty has emerged as a critical factor, particularly for organizations operating in regulated sectors or those prioritizing data privacy and control. Bilge Yücel, Sr. DevRel at deepset GmbH, delivered a presentation titled "What Breaks When You Build AI Under Sovereignty Constraints" at AI Engineer Europe, shedding light on the complexities and considerations involved in developing Sovereign AI systems. Visual TL;DR. AI Sovereignty Need leads to Engineering Challenges. Engineering Challenges addressed by Four Pillars. Four Pillars leads to Data Sovereignty. Four Pillars leads to Model Sovereignty. Four Pillars leads to Infrastructure Sovereignty. Four Pillars leads to Operational Sovereignty. Engineering Challenges with Solutions Provided. Solutions Provided using Haystack Integration. Haystack Integration enables Sovereign AI Systems. * AI Sovereignty Need: organizations need control over data, models, infrastructure, operations * Four Pillars: data, model, infrastructure, and operational control are key * Data Sovereignty: governs how data is accessed and used in AI systems * Model Sovereignty: control over the choice and development of AI models * Infrastructure Sovereignty: control over the underlying hardware and software stack * Operational Sovereignty: control over the deployment and ongoing management of AI * Engineering Challenges: complexities in building AI under sovereignty constraints * Solutions Provided: addressing challenges with specific engineering approaches * Haystack Integration: bringing it all together with deepset's Haystack framework * Sovereign AI Systems: design, deploy, and operate AI on own terms Visual TL;DR Understanding Sovereign AI. Yücel defined Sovereign AI as the ability of an organization to design, deploy, and operate AI systems on its own terms. This entails having explicit control over data flow, model choice, infrastructure, and operations. She broke down the concept into four key pillars: Data Sovereignty, Model Sovereignty, Infrastructure Sovereignty, and Operational Sovereignty. The Four Pillars of Sovereign AI. Data Sovereignty governs how data is accessed and used in AI systems, emphasizing that data should be stored and processed within trusted jurisdictions to meet compliance requirements, and that access permissions must be respected. Yücel highlighted that for European citizens, data sovereignty often means data must remain within Europe, citing GDPR as a prime example.

In order to optimally implement credX's expertise in the application, credX is working together with AI specialist Deepset