DataFlint

DataFlint is a suite of AI agents built specifically for Apache Spark that connects to a team's production environment, reading Spark logs, cluster metrics, and job history to find performance bottlenecks and cost issues. Its Agentic Spark Copilot lives inside IDEs like VS Code, Cursor, and IntelliJ, where it can trace a failing or slow job back to its root cause and propose code-level fixes with full production context through a Spark MCP server. A separate Cluster Agent right-sizes compute resources in real time, a Review Agent flags performance regressions inside pull requests before they reach production, and a Fleet Observability dashboard gives cost attribution across an organization's Spark jobs. It works across AWS EMR, Databricks, Google Dataproc, Microsoft Fabric, and Kubernetes, and reads from storage systems including S3, Azure Blob Storage, HDFS, and GCS. DataFlint is aimed at data engineers and platform teams running Spark at scale who want to cut both runtime and infrastructure spend without manually digging through Spark UI logs. The company reports customer results such as a 100x cost reduction and 13x faster execution for one client, though these are vendor-reported case studies rather than independently verified benchmarks, and pricing details beyond a free trial are not published on the site.