October 9, 2025 — Leads & Copy — Ataccama, the AI-powered data trust company, has launched Data Quality Gates, an extension of its data quality suite designed to validate data in motion across modern data stacks. This new capability applies rules in real-time, intercepting unfit inputs before they can negatively impact analytics, compliance reporting, or AI models.
As AI adoption grows and regulations like the EU AI Act and SEC reporting standards increase the need for data integrity, companies can no longer afford to discover data problems after the fact. Gartner reports that poor data quality costs organizations $12.9 million annually due to wasted spending, compliance risks, and loss of trust.
Ataccama Data Quality Gates prevent issues upstream by running checks in real-time as data flows through pipelines, preventing invalid records from contaminating downstream systems. Flawed inputs are intercepted immediately, reducing remediation costs, lowering compliance risk, and ensuring AI and analytics are powered by trusted inputs. This approach bridges the gap between business teams and engineering pipelines, ensuring standards are applied consistently and automatically.
Jessica Smith, VP of Data Quality at Ataccama, stated that many failures in AI and compliance can be traced back to bad data flowing unchecked into critical systems. Data Quality Gates aims to prevent outdated or unfit data from entering these systems, protecting trust and ensuring important decisions are based on reliable data.
Key differentiators of Data Quality Gates include validation in motion, business rules where data flows, one governed rules library, bridging business and engineering, and cross-platform trust. These features ensure standards apply consistently across environments.
Ataccama makes data quality the engine of trust for modern AI and analytics by unifying checks on data at rest and in motion, allowing enterprises to scale confidently with accurate and reliable data.
Media Contact: press@ataccama.com
Source: Ataccama
