Confluent, Inc.CFLT

IBM and Confluent partner to provide real-time data fabric for AI agents with governance and controls.

“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 IBM and Confluent provide the fabric through which AI agents can access the information they need, with the controls, governance, and real-time velocity to put information to work safely and at scale.”

IBM MQ, webMethods, and Confluent enable event-driven automation for applications, APIs, and AI agents.

“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.”

Analyst quote on IBM portfolio for data governance and real-time streaming to support AI agents.

““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 Sanjeev Mohan, Principal Analyst, SanjMo . "IBM has made significant progress assembling a portfolio that addresses both sides of this equation: governance and infrastructure for data at rest, and a platform for data in motion. For enterprises whose architecture and priorities align with this approach, it is a compelling stack worth evaluating.””

Confluent states it supports customers' emerging agentic AI applications with its data streaming platform.

““Confluent delivered a strong fourth quarter to close the year, including 23% year over year growth in Confluent Cloud,” said Jay Kreps, co-founder and CEO, Confluent. “Our AI product advancements and continued innovation across our core offerings further strengthened our category leadership this quarter. We remain focused on delivering a complete data streaming platform to support our customers’ most mission-critical workloads, including emerging agentic AI applications.””

Emergence of generative AI and agentic event-driven systems increases importance of real-time data.

“Confluent is operating at the convergence of three major industry trends that we believe will drive continued adoption of the Data Streaming Platform. First, the emergence of generative AI and agentic, event-driven systems is elevating the importance of real-time, contextualized data. Using stale data for AI agents creates a latency gap that introduces risk and inaccuracy; AI systems and applications require a continuous supply of fresh context to make accurate, reliable decisions. Second, as organizations continue to invest in sophisticated analytical capabilities across data warehouses, data lakes, and analytics engines, the need for real-time, reusable data assets that can power both analytics and operations continues to grow. This convergence of the operational and analytical estates requires a unified platform that can serve trustworthy data to any destination, reducing the friction of disparate silos. And finally, open source technologies like Apache Kafka®, Apache Flink®, Apache Iceberg®, and Delta Lake have matured into enterprise-ready standards with widespread adoption that drive a virtuous cycle of technical expertise, community contributions, and proven production deployments. We believe each of these trends represents a significant opportunity for the Data Streaming Platform.”

Confluent launched Confluent Intelligence and Streaming Agents for building event-driven AI agents.

“We have significantly expanded our capabilities to bridge the historic divide between the operational data that runs businesses and the analytical and AI systems that automate them. To seamlessly connect real-time operations with the data lakes and warehouses that power modern analytics, we introduced Tableflow, which materializes data streams directly into open table formats like Apache Iceberg and Delta Lake. Tableflow was designed to ensure that analytical engines can query fresh, governed data without the friction of complex, custom-built pipelines. Building on our foundation of Kafka and Flink, we also developed Confluent Intelligence, a suite of features built to address critical AI data needs by bringing real-time data directly to production AI systems. These features enable organizations to build event-driven AI agents that act on fresh data, while simultaneously serving the trustworthy context those agents require to make accurate decisions. Together, these innovations are designed to ensure that both analytics and AI applications are not limited by stale data, but are continuously fed by high-fidelity, up-to-date context, transforming our platform into the essential data foundation for the intelligent enterprise.”

Customer journey supports adoption of data platform for AI and analytics use cases.

“Confluent has built an operationalized customer journey, which we call our Data Streaming Journey, that ties together product features, go-to-market efforts, and customer success capabilities. This progression helps take customers from their initial experiments with the technology to organization-wide adoption as one of their most critical data platforms. This starts by landing use cases in a high volume, low-friction manner while projects are still being conceived and the architecture of the solution is being designed. Awareness and use of our offerings begin even before our sales efforts, given the widespread adoption of Apache Kafka by developers and the self-service adoption made possible with our cloud product and community downloads. Our enterprise sales force takes these initial engagements and helps users progress to production use cases and paying customers either on a pay-as-you-go model or with a committed contract. Once customers see the benefits of our product for their initial use cases, they often expand into other use cases and lines of business, divisions, and geographies. Our deep technical expertise, coupled with our product capabilities and laser focus on customer outcomes, enable us to form strategic partnerships with our customers on this journey. This expansion is helped by a natural network effect in which the value of our platform to a customer increases as more use cases are adopted, more applications and systems are connected, and more data is added”

Confluent launched Confluent Intelligence including Streaming Agents for real-time AI agents.

“• We launched Confluent Intelligence, a suite of capabilities designed to bring trusted, real-time data to AI use cases. This includes our Real-Time Context Engine, which enriches AI systems and applications with trustworthy, contextualized data, and Streaming Agents, which allow customers to build AI agents that can autonomously observe, decide, and act on business events in real time.”

Confluent positions its data streaming platform to support customers' real-time agentic AI applications.

“• Underpin our Customers’ Generative and Agentic AI Transformations : Companies are increasingly assessing and adopting AI solutions to embed in their operations and in their products. In the enterprise context, these technologies are only as useful as their ability to access and interact with company data and systems in a trusted and timely manner. In some cases, applications will not be time sensitive and will rely on data updated periodically through batch processes. In many cases, however, AI applications will demand data that is up-to-date and captures the real-time state of the business, its customers, and the market landscape. Confluent’s Data Streaming Platform is uniquely positioned to support the next generation of AI applications by enabling real-time, event-driven architectures ideal for coordinating and orchestrating autonomous agents. This approach overcomes the limitations of batch processing, allowing AI systems to operate on the freshest, most relevant data. By integrating AI applications with real-time streaming data, customers can drive real-time personalization, decision-making, and scalable, flexible architectures that evolve alongside AI advancements. Confluent is well positioned to meet the growing demand for AI-driven solutions across various industries.”

Confluent plans to expand into ML, generative and agentic AI use cases built on its data streaming platform.

“• Grow Further Use Cases Up-The-Stack Leveraging our Strategic Position for Data Streaming. Data streaming is a disruptive new platform technology, and as such there are countless use-case focused opportunities up the stack. After landing an initial workload, we expand across additional enterprise use cases, from horizontal IT (pipelines to cloud databases/warehouses, microservices, mainframe integration) to industry-specific scenarios like real-time fraud detection, creating a network effect as each new application connects to the streams already in place. As this footprint grows, Confluent increasingly operates as the central nervous system for data in motion, which strategically positions us to move up the stack into use case-specific adjacencies that apply data streaming, spanning ML, generative and agentic AI, IoT, real-time analytics, real-time logistics, customer data unification, cloud migration, data sharing, and more. Each subsequent project is delivered faster and at lower cost, reinforcing a flywheel of adoption that permeates the enterprise and drives further demand for data streaming.”

IBM acquires Confluent to deliver data platform for applications and AI agents.

“$11B acquisition to deliver end-to-end data platform for businesses to connect, process and govern data for applications and AI agents”

IBM and Confluent will integrate applications, data systems and AI agents in hybrid cloud.

“IDC estimates that more than one billion new logical applications will emerge by 2028 [1] , reshaping technology architectures across industries. To fuel meaningful outcomes and drive productivity in operations, these applications, as well as AI agents, need access to connected and trusted data – in real time. IBM and Confluent will enable end-to-end integration of applications, analytics, data systems and AI agents to drive intelligence and resilience in hybrid cloud environments.”

IBM states acquisition of Confluent will enable enterprises to deploy generative and agentic AI.

““IBM and Confluent together will enable enterprises to deploy generative and agentic AI better and faster by providing trusted communication and data flow between environments, applications and APIs. Data is spread across public and private clouds, datacenters and countless technology providers,” said Arvind Krishna, IBM chairman, president and chief executive officer. “With the acquisition of Confluent, IBM will provide the smart data platform for enterprise IT, purpose-built for AI.””

Confluent CEO notes platform supports generative and agentic AI before joining IBM.

““Since its founding, Confluent has helped organizations unlock the full potential of their data, driving innovation in an increasingly complex IT landscape. We are extremely proud of the work we’ve done in providing clients with a real-time data streaming platform for the next era of technology, including generative and agentic AI,” said Jay Kreps, CEO & Co-founder, Confluent. “We are excited by the potential to join IBM and to accelerate our strategy with IBM’s go-to-market expertise, global scale and extensive portfolio. I look forward to the future we will build together as Confluent becomes part of IBM.””

Confluent platform prepares data for AI and eliminates silos inherent in agentic AI.

“The real-time nature of Confluent’s platform is critical for organizations as they leverage data living across all IT environments. Confluent addresses the challenges of today’s technology and data landscape. Confluent excels at preparing data for AI, keeping it clean and connected across systems and applications, eliminating silos inherent in agentic AI. In the last four years alone, Confluent’s total addressable market (TAM) has doubled from $50 billion to $100 billion in 2025 [2] . Confluent’s real-time data and event streaming capabilities, combined with IBM’s AI infrastructure software and Automation offerings, will better position the companies to capture this opportunity.”

Confluent positions its data streaming platform to support real-time AI and agentic applications for customers.

“Underpin our Customers’ Generative and Agentic AI Transformations : Companies are increasingly assessing and adopting artificial intelligence (AI) solutions to embed in their operations and in their products. In the enterprise context, these technologies are only as useful as their ability to access and interact with company data and systems in a trusted and timely manner. In some cases, applications will not be time sensitive and will rely on data updated periodically through batch processes. In many cases, however, AI applications will demand data that is up-to-date and captures the real-time state of the business, its customers, and the market landscape. Confluent ’ s Data Streaming Platform is uniquely positioned to support the next generation of AI applications by enabling real-time, event-driven architectures ideal for coordinating and orchestrating autonomous agents. This approach overcomes the limitations of batch processing, allowing AI systems to operate on the freshest, most relevant data. By integrating AI applications with real-time streaming data, customers can drive real-time personalization, decision-making, and scalable, flexible architectures that evolve alongside AI advancements. Confluent is well positioned to meet the growing demand for AI-driven solutions across various industries.”

Confluent sees potential customer adoption of use cases including generative and agentic AI that will drive data streaming demand.

“Grow Further Use Cases Up-The-Stack Leveraging our Strategic Position for Data in Motion. Data in motion is a disruptive new platform technology, and as such there are countless use-case focused opportunities up the stack. As we grow into our role as a central nervous system within companies, we believe we have an incredibly strategic position from which to grow into use-case specific adjacencies that apply data in motion. We see the potential for broad, cross-industry customer adoption of use cases around machine learning, generative AI, agentic AI, IoT, data integration, real-time analytics, real-time logistics, customer data unification, cloud migration, microservices, data sharing, as well as countless others. We believe that increased adoption of these use cases will also drive demand for data streaming.”