Celonis, the pioneer and global leader in Process Intelligence, announced a strategic expansion of its collaboration with Amazon Web Services (AWS). This joint initiative is designed to equip organizations with the deep operational context required to transition AI deployments from experimentation to measurable corporate value. Through a newly introduced zero-copy connection, enterprises can now seamlessly unify the robust cloud storage and data governance of Amazon S3 and AWS Glue with the enterprise-grade Celonis Platform.
As businesses increasingly demand direct financial returns from their artificial intelligence investments, the integration addresses critical barriers in data engineering.
By bridging Celonis with AWS, the collaboration unlocks several operational advantages:
- ROI Focused AI Agents: With real-time operational context being streamed into Amazon Bedrock, companies can design intelligent AI agents that understand complex business processes, automate multiple workflows, and generate ROI.
- Fast Data Velocity: The architecture allows for data queries directly from Amazon S3, resulting in 5x to 10x faster performance of entire data pipeline than conventional data extraction methodologies.
- Reduction of Data Duplication: The zero-copy approach guarantees that all data is stored in one place. This not only saves on cloud storage costs but also avoids issues related to data replication.
- Security and Governance: The architecture is designed in such a way that it honors all security principles by using native connections with AWS Glue, Amazon S3 tables, and REST catalog of Apache Iceberg.
Technical deployment of this integration leverages the Iceberg REST Catalog alongside the Celonis Data Core the platform’s high-performance data engine. This allows the Celonis Process Intelligence Graph to read live, immutable data directly from Amazon S3. By supercharging raw storage data with operational intelligence, enterprises can effectively construct a dynamic digital twin of their entire corporate workflows. This process-centric foundation can then be fed into Amazon Bedrock to build and deploy production-ready AI agents that understand how the business actually flows.
“It’s time to move past the era of AI science projects to Enterprise AI that delivers meaningful business outcomes,” said Dan Brown, Chief Product Officer at Celonis. “By integrating with Amazon S3, we are drastically accelerating the time to value for our customers. We’re giving agents built with Amazon Bedrock the immediate, real-time operational context they need to make the right decisions, take the right actions, and drive real value fast.”
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“Customers don’t want to spend months migrating data before they can see value from AI they want to put their data to work where it already lives,” said Carol Potts, General. Manager, US ISV Sales, AWS. “This collaboration with Celonis makes that possible, bringing deep process intelligence directly to Amazon S3 and simplifying the stack so teams can focus on building smarter AI agents in Amazon Bedrock rather than managing complex pipelines. Together, we’re helping customers move faster from AI experimentation to real operational impact.”
Global enterprises are already looking to the architecture to refine large-scale operations. For heavy industry leaders managing complex global supply chains and manufacturing footprints, minimizing data latency while retaining governance is a critical operational priority.
“At BMW Group, turning massive volumes of process data into tangible operational impact is essential to continuously improving our manufacturing and enterprise processes,” said Marco Görgmaier, Vice President Data, Artificial Intelligence & Enterprise Platform. “The zero-copy connection between Celonis and AWS helps us to significantly reduce unnecessary data movement while maintaining control over our process data. It provides the process context needed for analytics, AI agents and automated workflows to identify improvement potential faster and support more efficient operations across the enterprise.”
