Celonis & AWS boost AI agents with S3 process data

Celonis and AWS have expanded their collaboration to connect the Celonis Process Intelligence platform with data stored in Amazon S3, giving AI agents direct access to operational context from business processes.

The integration allows Celonis to read live data in Amazon S3 without requiring customers to copy or migrate it into separate systems. Using the Iceberg REST Catalog, Celonis' Process Intelligence Graph can work directly with data where it already sits in AWS environments.

The companies are addressing a common problem in corporate AI projects: large language models can generate responses but often lack an understanding of how work moves across business systems, departments and workflows. Celonis says adding process intelligence to operational data creates a digital representation of how a business actually runs, which can then be used with Amazon Bedrock to build AI agents.

This architecture is intended to reduce the need for extraction and replication pipelines that move data between platforms before it can be used. Direct querying of data in Amazon S3 can deliver end-to-end pipeline performance five to 10 times faster than traditional approaches, according to Celonis.

Celonis also says the model cuts data duplication, lowers storage costs and reduces synchronisation issues by maintaining a single source of truth within AWS. For companies trying to govern data across multiple systems, that could remove one of the more cumbersome layers in AI deployment.

Process context

Celonis has built its business around process mining and process intelligence software that analyses event data from enterprise systems to show how processes function in practice, rather than how they were designed. By linking that view to data held in Amazon S3, the company aims to bring operational process context closer to the tools businesses use to develop generative AI applications.

The announcement also reflects a broader push by cloud providers and software vendors to present clearer business use cases for AI beyond pilots and internal tests. Businesses have invested heavily in large language models and generative AI services, but many still face basic problems with data access, quality and context when moving into day-to-day operations.

Dan Brown, Chief Product Officer at Celonis, said: "It is time to move past the era of AI science projects to Enterprise AI that delivers meaningful business outcomes. 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."

AWS described the arrangement as a way for customers to use existing data without lengthy preparation work, noting that many businesses want to avoid moving large data sets before testing or deploying AI systems.

Carol Potts, General Manager, US ISV Sales at AWS, said: "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.

"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."

Customer use

BMW Group is among the companies using the technology. The manufacturer said the set-up is relevant in environments where large volumes of process data must be turned into measurable operational changes across manufacturing and wider business functions.

Marco Görgmaier, Vice President Data, Artificial Intelligence & Enterprise Platform, said: "At BMW Group, turning massive volumes of process data into tangible operational impact is essential to continuously improving our manufacturing and enterprise processes.

"The zero-copy connection between Celonis and AWS helps us 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."