definity Unveils Agentic Data Engineering Platform With $12M Series A
Agentic platform enabling data lakehouse teams to reduce platform costs, improve reliability, and accelerate data and AI delivery
The Operational Gap in Modern Data Platforms
Enterprise data platforms now underpin AI, analytics, and core business operations. Data engineering teams are expected to deliver faster while maintaining production reliability and controlling costs across increasingly complex environments.
However, most teams still operate with fragmented tooling that monitors isolated signals – data quality, execution health, infrastructure performance, or spend – after the fact and without a unified operational context. As a result, data engineering remains reactive and manual, and more importantly, AI agents lack the runtime understanding required to take effective action and operate safely in production environments.
The outcome is disastrous – significant infrastructure waste, recurring pipeline incidents, and slow data delivery that constrains business outcomes.
definity was built to solve this operational gap.
From Monitoring to Agentic Operation
definity introduces a new operating model for enterprise data platforms: agentic data engineering.
The platform provides actionable runtime intelligence powering AI agents that enable teams to continuously optimize platform cost, prevent incidents before they impact the business, and dramatically increase developer velocity.
At the core of definity is an in-motion architecture that operates directly within production pipelines, without requiring code changes. By observing pipelines during execution, the platform captures full-stack signals across infrastructure behavior, pipeline execution, and data characteristics.
This unified runtime context, combined with the ability to safely control pipeline execution in real time, enables the shift from monitoring to true agentic operation.
Without runtime intelligence and control, AI agents remain advisory and post hoc. With it, they can autonomously analyze, optimize, and take action in production.
"As AI becomes embedded across the enterprise, data platforms can no longer be operated through fragmented, reactive tooling," said
Proven Enterprise Outcomes at Scale
Global enterprises use definity to reduce platform costs by more than 30 percent through job-level optimization, prevent pipeline and data incidents in motion before they impact the business, and resolve complex Spark issues 10 times faster.
The solution supports large lakehouse deployments across both cloud and on-premises Spark environments, including Databricks,
"definity brings much-needed intelligence to the data layer by applying runtime context across data pipelines," said
Funding to Scale Agentic Data Engineering
This round comes on the heels of significant momentum for definity, tripling its revenue over the past six months and adding several Fortune 500 and large enterprise customers.
The
"definity is solving a problem that becomes unavoidable at enterprise scale," said
As enterprise AI adoption accelerates, data platforms are under unprecedented operational strain. The ability to operate pipelines with full context and autonomous action is becoming essential. definity is the foundational infrastructure for this new era, enabling data engineering teams to move from fragmented monitoring and reactive alerts to proactive, autonomous operation of production data pipelines.
About definity
definity is the agentic data engineering platform for the lakehouse and Spark ecosystem, providing actionable runtime intelligence via AI agents that enable enterprise data engineering teams to optimize platform costs, proactively prevent job and data incidents, and improve developer velocity.
For more information, visit www.definity.ai.
View original content:https://www.prnewswire.com/news-releases/definity-unveils-agentic-data-engineering-platform-with-12m-series-a-302757245.html
SOURCE definity
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