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Definity puts agents inside Spark pipelines to stop failures before they poison agentic AI systems
Technology
Published on 30 April 2026
It can halt downstream jobs when upstream data turns stale
Definity says it is rethinking data pipeline reliability for agentic AI by embedding “in-execution” agents directly into Spark or DBT runs. Instead of alerting after jobs fail, the agents capture real-time execution context and can intervene mid-run—stopping downstream pipelines before stale or bad data spreads. The company also announced a $12 million Series A.
- Definity embeds JVM agents inside Spark or DBT to act during pipeline runs
- It captures execution context like memory pressure, skew, and shuffle patterns in real time
- Agents can intervene, stopping downstream jobs when upstream inputs are stale
- Series A funding totals $12 million, with customers reporting big troubleshooting gains
Read the full story at Venture Beat
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Venture Beat