Flarion is rebuilding the execution layer underneath the distributed data engines that enterprises have standardized on. Spark, Hadoop, and Ray are reliable and deeply embedded in production environments, but their architectures, JVM-based, row-oriented, designed for a different era of hardware, leave meaningful performance and cost on the table. The conventional path to closing that gap is painful: rewrite code to move onto a faster engine like Polars, migrate onto Apache Arrow, or absorb the operational overhead of managing a new stack. Flarion's approach is different. The company delivers Polars-level performance and Arrow-native execution to existing Spark, Hadoop, and Ray workloads through a plug-and-play engine that installs in minutes, requires no code changes, and runs as an in-process plugin inside the customer's environment. Unsupported operations fall back transparently to the underlying engine, so the acceleration layer is effectively invisible to the workload above it. The result for customers is up to 3x faster job execution, up to 60% lower infrastructure cost, and smaller, more stable clusters that fail less often.
The company was founded by Ran Reichman (CEO) and Udi Tizan (COO). Ran's background is in building data processing systems for mass-scale consumer applications and autonomous vehicles, environments where the economics of data processing directly shape what products are possible. Udi built and scaled GlobalDots from zero to $15 million ARR and previously worked on cloud infrastructure at Granulate, which exited to Intel for $650 million. Together they identified a consistent pattern across industries: organizations hitting both a performance and cost ceiling in their data processing, with infrastructure spend consuming up to 40% of IT budgets while legacy codebases made wholesale migration impractical. Flarion is the layer that lets enterprises modernize their data stack without touching it. The platform integrates across every major deployment of these engines, including Databricks, AWS EMR, GCP Dataproc, Azure HDInsight, Spark on Kubernetes, and Anyscale, and is available on the AWS Marketplace.