Confluent Cloud boosts agentic AI with enhanced data & security
The new capabilities for Confluent Cloud are centered around enhancing data quality, improving security, and simplifying networking for organisations deploying agentic artificial intelligence systems. The company has made these announcements as part of ongoing efforts to enable enterprises to better use their data assets for more effective decision making.
Snapshot queries
One of the key features highlighted is the availability of snapshot queries in Confluent Cloud for Apache Flink. This functionality brings together real-time and batch data processing, making it possible for artificial intelligence agents and analytics systems to work with historical and up-to-date information in a single environment. The objective is to deliver smarter and more informed business decisions by ensuring complete data context is always available. "Agentic AI is moving from hype to enterprise adoption as organizations look to gain a competitive edge and win in today's market," said Shaun Clowes, Chief Product Officer at Confluent. "But without high-quality data, even the most advanced systems can't deliver real value. The new Confluent Cloud for Apache Flink features make it possible to blend real-time and batch data so that enterprises can trust their agentic AI to drive real change."
The integration allows teams to use one product and one programming language to manage both streaming and historical datasets, removing the need to run separate tools or manual workarounds. Through seamless Tableflow integration, snapshot queries offer teams the ability to explore and analyse data comprehensively, enabling analytics and agentic AI to be informed by both past and present trends. This feature is now in early access for users.
Expert insights "The rise of agentic AI orchestration is expected to accelerate, and companies need to start preparing now," said Stewart Bond, Vice President of Data Intelligence and Integration Software at IDC. "To unlock agentic AI's full potential, companies should seek solutions that unify disparate data types, including structured, unstructured, real-time, and historical information, in a single environment. This allows AI to derive richer insights and drive more impactful outcomes."
Agentic AI has been increasingly adopted by businesses seeking to optimise efficiency and obtain faster insights by analysing diverse sets of data. Access to both historical and streaming information is essential for use cases such as fraud detection, where banks need to examine both current activities and previous transaction records, and in healthcare, where clinicians rely on real-time patient data alongside medical histories for informed decisions.
By enabling one platform to handle multiple data types seamlessly, Confluent aims to simplify workflows and reduce the operational complexity associated with managing separate data systems for AI and analytics initiatives.
Networking and security improvements
Addressing connectivity and security requirements, Confluent Cloud now includes the Confluent Cloud Network (CCN) routing feature. This improvement allows teams to repurpose existing CCNs, previously created for Apache Kafka clusters, to establish secure connections for Apache Flink workloads. CCN routing is now available on Amazon Web Services in all Flink-supported regions. This is intended to make it easier for organisations with strict internal network controls to deploy stream processing, AI agents, and analytics securely.
Confluent has also rolled out IP Filtering for Flink to grant more precise access control for hybrid environments. Many organisations have strict policies governing public data access, and this feature enables teams to restrict internet traffic to specific, allowed IP addresses while providing better visibility into unauthorised access attempts. IP Filtering is now generally available for all Confluent Cloud users.
The company's new features aim to help organisations transform their intended use of agentic AI into concrete benefits to their operations, offering additional options for private networking, expanded data source connectivity, and improved governance in stream processing environments.
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