Definity raises $12M to embed AI agents in Spark pipelines for data quality

Definity raises $12M to embed AI agents in Spark pipelines for data quality

Definity, a data infrastructure startup, has raised $12 million to integrate AI agents directly into Apache Spark pipelines. These agents monitor data flows in real time, detecting anomalies, schema drift, and bad data before they propagate to downstream agentic AI systems. The funding will be used to expand engineering and go-to-market efforts.

This investment highlights a capital-compression pattern in data infrastructure: startups are converging on the same problem—ensuring reliable data for AI—but through different technical approaches. Definity embeds agents inside the pipeline rather than relying on external monitoring tools, potentially reducing latency and simplifying adoption for enterprises already using Spark. As agentic AI systems become more autonomous, the cost of data failures rises sharply, making pipeline-level observability a strategic necessity.

The move also reflects the broader hyperscaler-distribution moat battle. AWS, Google, and Databricks all offer native data quality tooling for Spark. Definity's agent-based detection may carve a niche by catching failures earlier, but it will need to integrate tightly with major clouds to avoid being squeezed out. At $12 million, the round is modest but sufficient to prove the approach with early enterprise customers.