Qualytics partners with Databricks to deliver proactive, automated data quality natively on the Databricks Data Intelligence Platform, enabling trusted, AI-ready data without data leaving the lakehouse
Qualytics, the augmented data quality platform built for enterprises, announced a technology partnership with Databricks, the Data and AI company. Through this partnership, organizations can now run Qualytics natively on the Databricks Data Intelligence Platform, ensuring their data is accurate, explainable, and AI-ready without requiring external processing outside their Databricks environment.
With Qualytics and Databricks, companies benefit from automated rule creation, adaptive intelligence for data quality, and deep row-level anomaly detection, enabling them to proactively manage data quality directly at enterprise scale.
Databricks provides the backbone for analytics and AI. Qualytics ensures the data fueling those workloads is trustworthy from the start. With more than 95% of rules automatically generated and maintained by Qualytics, data teams can replace reactive cleanup with proactive control, catching issues before they impact dashboards, models, or downstream systems.
Because Qualytics runs directly on the Databricks Data Intelligence Platform, customer data never leaves Databricks, meeting strict security, governance, and compliance requirements while accelerating time-to-value.
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“Databricks gives teams incredible power and flexibility. With Qualytics in the lakehouse, that power is paired with continuous data trust,” said Gorkem Sevinc, co-founder & CEO of Qualytics. “Data quality has historically been reactive and slow. Together with Databricks, we’re helping enterprises take control of their data early so AI, analytics, and operational decisions are built on data they can inherently trust.”
Qualytics offers first-class support for Databricks, integrating with Delta Lake, Lakeflow Jobs, Databricks SQL, and Unity Catalog to ensure data quality. This allows teams to detect anomalies in near real-time and enable proactive remediation workflows within the tools they already use.
Every profiling run, anomaly scan, or rule evaluation executed through Qualytics runs inside native Databricks Lakeflow Jobs. This ensures the platform fits naturally into existing lakehouse operations without adding new architectural overhead, data egress costs, or data security and privacy concerns.
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“Customers want trusted data, and they want it without adding complexity or compromising on governance,” said Eric Simmerman, CTO and Co-Founder of Qualytics. “Running inside Databricks means we meet teams exactly where their data lives. They get adaptive intelligence, deep anomaly detection, and enterprise governance without data egress or replication.”
The Qualytics + Databricks integration is available today. Existing Databricks customers can deploy Qualytics as a native workload inside their environment and begin generating automated rules, profiling metadata, and detecting anomalies in hours, not months.
