Your data's first line of defense.
AI-powered data reliability monitoring that detects anomalies, ensures quality, and protects your data before issues cascade.
SELECT DISTINCT * FROM transactions WHERE timestamp > NOW() - INTERVAL '1 hour'Real-time monitoring of data patterns with intelligent anomaly detection and alerting.
Suggested fixes and automated responses to common data quality issues.
Confidence metrics for every dataset, updated continuously as data flows.
Continuous monitoring and intelligent anomaly detection across your entire data pipeline
Connects to your data pipelines and establishes baseline patterns for volume, schema, distribution, and latency metrics.
AI models continuously compare incoming data against baselines, detecting statistical anomalies and pattern deviations in real-time.
Automatically gates suspicious data, alerts teams with actionable context, and suggests remediation strategies.
Advanced AI reasoning that understands your data's behavior patterns and context
Builds dynamic baselines that adapt to seasonal patterns, business cycles, and gradual data evolution
Sophisticated scoring that separates true anomalies from expected variance and noise
Traces anomalies back to root causes across complex data lineage and dependencies
Learns from human feedback and adjusts sensitivity based on operational outcomes
Distributed monitoring system with ML-powered anomaly detection and automated quality assurance
Multi-Source Collection
ML-Powered Detection
Automated Actions
Horizontally scalable with automatic sharding and load balancing across clusters
Multiple specialized models for different anomaly types with continuous learning
Auto-discovery of schemas and relationships with intelligent baseline generation