Explainable Data Quality using AI. Fully automated.

Agentic AI in data quality means AI systems that autonomously monitor, detect, and explain data issues without constant human supervision. Anode's agentic AI continuously scans your data, identifies 6 classes of anomalies (Class 1: Data Type Anomalies, Class 2: Abnormal Values, Class 3: Categorical Anomalies, Class 4: Numeric Anomalies, Class 5: Typos, Class 6: Blank Values), and provides explainable insights about why each issue was flagged.

Traditional data quality tools require manual rule writing and constant maintenance. Anode uses AI to automatically learn your data patterns and detect anomalies without predefined rules. It provides explainable AI insights - telling you exactly why something is flagged - helping your team focus on genuine issues rather than false alarms.

Anode detects 6 comprehensive classes of anomalies: (1) Data Type Anomalies - values not matching the column's datatype (e.g., text in numeric columns), (2) Abnormal Values - values not matching column identity (e.g., non-countries in a country column), (3) Categorical Anomalies - proportionally rare values (e.g., if most values are 'USA', minority values like 'UK' are flagged), (4) Numeric Anomalies - outlier numbers outside the normal range, (5) Typos - spelling mistakes and typographical errors (English language), and (6) Blank Values - missing data in columns. Anode's AI automatically learns what's normal for each column and flags deviations.

Yes, explainability is Anode's core strength. Unlike black-box AI solutions, Anode provides natural language explanations for every alert, showing confidence scores, highlighting specific problem areas, and explaining the reasoning. This builds trust with your team and enables quick, informed action on data quality issues.

Anode assigns a quality score (0-1) to every row of data, where 1 means perfect quality and lower scores indicate issues. The AI engine analyzes multiple dimensions including completeness, accuracy, consistency, and timeliness. Your team gets a real-time dashboard showing overall data health and can drill down to specific problem records.

Anode supports both real-time streaming data and batch processing. For real-time use cases, Anode continuously monitors data streams and provides instant alerts when quality degrades. For batch scenarios, it validates data files before they're loaded into your systems, preventing bad data from entering your analytics.

Anode integrates with major databases (PostgreSQL, MySQL, SQL Server, Oracle), cloud data warehouses (Snowflake, BigQuery, Redshift, Databricks), data lakes (S3, Azure Data Lake), and streaming platforms (Kafka, Kinesis). It can monitor data quality across your entire data ecosystem from a single platform.

Anode provides automated data governance with audit trails, data lineage tracking, and compliance reporting for regulations like GDPR and HIPAA. It flags data privacy violations, tracks who accessed sensitive data, and maintains historical quality metrics for compliance audits. Enterprise features include role-based access control and encrypted data processing.

Anode uses advanced AI algorithms to minimize false positives while catching genuine data quality issues. The system continuously learns from your feedback to improve detection accuracy over time. This means your team spends time fixing real problems, not chasing false alarms. Our explainable AI approach helps you understand why each issue was flagged, building confidence in the system.

Most customers have Anode monitoring their first data source within hours. Connect your data source, and Anode's AI automatically profiles your data, learns normal patterns, and starts detecting issues. No manual rule writing required. Full enterprise deployment typically takes 1-2 weeks including team training and custom workflow integration.