Conduktor Trust is a SaaS-based data quality and governance platform designed to enforce data quality at the point where streaming data is produced, particularly for Apache Kafka environments. It allows organizations to define and centrally manage quality rules using CEL (Common Expression Language), apply policies across all data streams, and trigger real-time actions—such as logging or blocking—when data violates these rules. Trust provides operational insights by tracking violations and patterns over time, enabling teams to prioritize fixes and continuously improve data quality. The platform supports both schema and schema-less topics, unifies quality, observability, and control, and reduces the burden on developers by shifting governance to a centralized, policy-driven approach. This proactive enforcement ensures that only high-quality, compliant data enters downstream systems, protecting AI models, analytics, and operational processes from the risks of bad data.

Key Features

Centralized Rule Definition and Enforcement Define and manage data quality rules using CEL.

• Enforce structure, completeness, and conformance at the source.
• Apply policies across all Kafka topics and environments.

Real-Time Policy Actions Trigger immediate actions when data quality rules are violated.

• Log or block problematic data before it enters pipelines.
• Prevents downstream issues and reduces remediation costs.

Operational Insights and Monitoring Track and analyze data quality violations over time.

• Identify recurring issues and prioritize fixes.
• Gain visibility into data quality across teams and systems.

Support for Schema and Schema-less Topics Works with both structured and unstructured streaming data.

• Ensures comprehensive coverage for all Kafka topics.

Producer-Led Enforcement (Data Contracts) Quality is enforced at the data source, not just downstream.

• Reduces developer friction and centralizes governance.

Benefits

Proactive Data Quality Assurance Prevents bad data from entering critical systems.

• Protects AI, analytics, and operational processes from data issues.
• Reduces time and cost spent on downstream remediation

Centralized Governance and Compliance Unifies data quality, observability, and control.

• Simplifies policy management and enforcement.
• Enhances compliance with regulatory and internal standards.

Improved Trust and Business Outcomes Ensures data is trustworthy, accurate, and ready for real-time use.

• Boosts confidence in AI, personalization, and predictive analytics.
• Supports mission-critical operations with reliable data.