IBM Completes Acquisition of Confluent, Making Real Time Data the Engine of Enterprise AI and Agents
Day-one integrations include
As enterprises move from AI experimentation to production, the critical barrier to success is the data — clean, governed, continuously refreshed —and delivered at the speed and scale AI demands. Yet in most enterprises today, data remains siloed across systems and environments, arriving hours or days after it is generated. Together
IDC estimates that more than one billion new logical applications will emerge by 2028 [1], driven by a new generation of AI that will only deliver value if the data behind it is live, trusted, and continuously flowing. That scale of demand requires a new kind of data foundation, and
"Transactions happen in milliseconds, and AI decisions need to happen just as fast. With Confluent, we are giving clients the ability to move trusted data continuously across their entire operation so their AI models and agents can act on what is happening right now, not on data that is hours old," said
Built on Apache Kafka®, the standard for data streaming, Confluent is already embedded in the operational fabric of the world's largest enterprises, with a customer base that spans industries from financial services and healthcare to manufacturing and retail.
- Michelin relies on Confluent to manage real-time inventory across a supply chain spanning 170 countries — achieving 35% cost savings without sacrificing visibility or control [2].
- L'Oréal uses Confluent to stream real-time product and inventory updates across internal systems and third-party applications, helping the company respond faster to changing consumer demand [3].
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BMW Group streams IoT data from 30+ production sites and its global sales network in real time, connecting factory floor systems and cloud applications across the organization [4]. - Ticketmaster streams ticket inventory, sales, and customer activity in real time across hundreds of systems, reducing development friction and powering machine learning at scale [5].
"Since our founding, Confluent's mission has been to set the world's data in motion, making data streaming as foundational to the enterprise as the database. Joining
Today's announcement brings immediate integrations across the
- AI-Ready, Real-Time Data. Enterprise AI technologies need current context, not yesterday's data. Confluent streams live operational events directly into watsonx.data – ensuring every model, agent, and workflow runs on continuously updated enterprise data, with lineage, policy enforcement, and quality controls included.
- Activate the modernized mainframe in the AI era. The most critical business transactions in the world have long run on IBM Z. With IBM Z and Confluent, organizations can identify and drive real-time events at the transaction source as well as stream transactional data directly for real-time analytics, automation, and AI workflows. This enables mission-critical transaction processing to integrate tightly with the rest of the business in real-time, at enterprise scale.
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Event-Driven Automation Across Hybrid Environments. IBM MQ and
IBM webMethods Hybrid Integration form the foundation of enterprise event-driven automation, combining trusted transactional messaging with modern integration and orchestration across hybrid environments. Confluent extends this platform with high-scale event streaming, enabling applications, APIs, and AI agents to sense and act on business events in real time.
With Confluent,
"The shift from AI experimentation to production deployment has exposed a critical gap in enterprise data architecture: the inability to deliver trusted, real-time data to the systems that need it most. AI agents and automated workflows don't operate on historical data; they require live operational signals, continuously flowing across the enterprise as events occur," said
Under the terms of the agreement,
For more information about today's news, please visit https://www.ibm.com/products/confluent
[1]
*Source: IDC, 1 Billion New Logical Applications: More Background, doc #US51953724,
[2 -5] *Source: Confluent Case Studies & Testimonials
https://www.confluent.io/customers/michelin/
https://www.confluent.io/customers/loreal/
https://www.confluent.io/customers/bmw-group/
https://www.confluent.io/customers/ticketmaster/
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Forward-Looking Statements
Certain statements contained in this communication may be characterized as forward-looking under the Private Securities Litigation Reform Act of 1995. These statements involve risks, uncertainties and other factors that could cause actual results to differ materially from those expressed or implied. Forward‑looking statements in this press release may include statements regarding the expected benefits of the transaction, the impact of the transaction on
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