Ensuring Data You Can Trust , Every Record, Every Stream, Every Decision.
Ensuring Data You Can Trust , Every Record, Every Stream, Every Decision.
Data-driven organizations rely on accuracy, consistency, and integrity , yet enterprise datasets often suffer from duplication, corruption, and schema drifts that compromise insights and compliance. Xevyte’s AI Data Quality & Validation Platform brings automation and intelligence to the forefront of data governance.
By combining machine learning, semantic understanding, and statistical validation, the platform continuously monitors, detects, and resolves quality issues across every source. It adapts to evolving data landscapes, learning from patterns to predict and prevent future anomalies. Whether your data flows from ERP systems, warehouses, or external APIs, Xevyte ensures it remains clean, consistent, and analytics-ready at all times.
Xevyte’s Data Quality & Validation Platform ensures high-integrity data across all enterprise systems through AI-powered profiling, anomaly detection, correction, and schema validation.
Gain instant visibility into data quality with automated, AI-powered profiling. Xevyte evaluates datasets across completeness, conformity, consistency, and accuracy metrics, providing an in-depth health score for each dataset. Its profiling models detect hidden correlations, outliers, and irregularities that traditional rules often miss. Interactive dashboards highlight data distribution, missing fields, and trend shifts for continuous oversight. The process runs autonomously at scale, enabling data teams to profile terabytes of data without manual effort or performance trade-offs.
Detect and respond to data anomalies before they impact business outcomes. Xevyte’s adaptive machine learning algorithms learn baseline behavior from historical datasets and flag deviations in real time. Whether it’s unexpected transaction spikes, sudden null-value surges, or cross-field inconsistencies, the platform triggers automated alerts through integrated channels like Slack, Teams, or ServiceNow. Alerts are ranked by severity and accompanied by contextual explanations to speed up root-cause analysis. This proactive anomaly detection helps maintain operational continuity and data accuracy across pipelines.
Automate the cleansing process with context-aware correction and intelligent deduplication. Xevyte applies semantic similarity scoring and entity-matching algorithms to identify and unify duplicate or conflicting records across multiple sources. It automatically standardizes data formats , from dates and currencies to geographic and categorical fields , ensuring uniformity across systems. Corrections are guided by configurable business rules and validation checkpoints for auditability. With each cycle, the system learns from prior corrections, continuously improving its accuracy and adaptability.
Stay ahead of change with real-time schema drift detection and rule validation. Xevyte continuously monitors source and destination systems to detect field additions, deletions, or type mismatches that could break pipelines. Automated impact analysis highlights affected downstream datasets, reports, or APIs. The platform enforces governance policies by validating data against defined business rules, ensuring structural and logical integrity. Version-controlled rule sets make it easy to track historical compliance and restore prior schema configurations when needed.
Embed data quality checks directly into your existing workflows with seamless integration. Xevyte natively connects to major ETL tools, orchestration frameworks, and BI platforms, including Airflow, Snowflake, Databricks, Power BI, and Tableau. The platform’s APIs and SDKs allow validation nodes to be inserted at any point in the data lifecycle. This ensures that errors are intercepted and resolved early in the pipeline, improving downstream reliability. Flexible deployment options (SaaS, VPC, or on-prem) provide scalability and security without infrastructure complexity.
The platform continuously enhances data integrity using AI-powered profiling, anomaly detection, and correction models that adapt to evolving datasets. It integrates seamlessly into modern data stacks, enabling real-time validation across pipelines without disrupting existing workflows.
Learns data patterns and continuously refines validation models to deliver accurate, contextual quality insights with minimal human supervision.
Built to fit into any modern data ecosystem , connecting effortlessly with existing pipelines, data warehouses, and governance tools.
Adaptive intelligence that evolves with changing business logic, ensuring future-proof data quality operations across domains.
Every validation, correction, and alert is logged with full lineage tracking, ensuring audit readiness for regulatory standards like GDPR, ISO 8000, and SOC 2.
Quality insights are tied directly to business KPIs , providing measurable improvements in operational efficiency, accuracy, and trust.