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New Striim 5.2 release introduces native real-time AI agents for predictive analytics, data governance, and vector embeddings—modernizing enterprise pipelines across multi-cloud and legacy sources

August 18, 2025 //  by Finnovate

With an ever-expanding multi-cloud data estate, enterprises are grappling with brittle data pipelines, ETL based batch lag, lack of automated agents, and siloed data architectures that are complex to integrate. Striim’s latest product release: Striim 5.2, empowers enterprises to close this gap by adding new endpoint connectors such as Neon serverless Postgres, IBM DB2 z/OS, Microsoft Dynamics and others. It delivers native, real-time, automated AI agents that augment data pipelines without adding operational complexity. This release also adds real-time support for legacy integration from mainframe sources, and data delivery into serverless PostgreSQL and open lakehouse destinations. Striim 5.2 introduces new capabilities to enable AI across three strategic pillars — Enterprise Modernization and Digital Transformation, Data Interoperability, and Real-Time AI — enabling data and analytics/AI teams to accelerate their next generation application roadmap without rewriting it from scratch. Key highlights include: Accelerating Real-time AI: Striim is taking major strides to bring AI directly into real-time data pipelines and applications. Striim recently released the Sherlock and Sentinel AI agents to enable in-flight sensitive data governance. With 5.2., Striim is introducing two new AI agents – Foreseer for anomaly detection and forecasting, and Euclid for real-time vector embedding generation – enabling teams to embed intelligence directly into data streams. Striim is also expanding support to AI-ready databases like Crunchy Data and Neon, built to handle AI agent workloads and in-database AI applications. Driving Enterprise Modernization: Striim now supports reading data in real-time from IBM DB2 on z/OS, making it easier for organizations to modernize their legacy systems. Enterprises can integrate their mainframe data to the cloud and build high-throughput data pipelines that can read data in real-time from a wide array enterprise-grade systems, such as: IBM DB2, Oracle, Snowflake, SQL Server and others, powering analytics, applications, and insights across the business. Powering Digital Transformation: Enterprises are increasingly using Apache Iceberg to provide data interoperability to break data silos, build broad ecosystem adoption, and to future-proof their data architectures. In addition to Delta, Stiim now supports writing data in the Iceberg format to cloud data lakes and to cloud data warehouses such as Snowflake and Google BigQuery. Customers can easily extend their existing data pipelines to take advantage of Iceberg tables without having to rearchitect their applications.

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Category: Data Economy & Privacy, Innovation Topics

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