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Automated data quality monitoring with AI
Anomalo is an AI-powered data quality platform that automatically monitors data in the warehouse for anomalies, errors, and issues without requiring teams to write and maintain rules for every table. It uses machine learning to learn normal patterns, detect unexpected changes, and explain root causes, alerting data teams to problems like missing data, distribution shifts, and broken pipelines before they impact downstream users.
Anomalo is used by data teams at organizations that want broad, low-effort data quality coverage across many tables rather than hand-writing tests. Its automated monitoring scales to large data estates, its root-cause explanations speed resolution, and its integrations connect to major warehouses. For teams seeking automated, ML-driven data quality at scale, Anomalo is a leading platform.
Pricing Model
PAID
Starting Price
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Free Options
Free trial
| Feature | Team Popular | Enterprise |
|---|---|---|
| Automated data monitoring | — | |
| Anomaly detection | — | |
| Root-cause analysis | — | |
| Warehouse integration | — | |
| Alerting | — | |
| Everything in Team | — | |
| Large-scale coverage | — | |
| Advanced ML checks | — | |
| Governance | — | |
| Dedicated support | — |
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API Types
SDK Availability
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Compliance Standards
SOC 2 Type II
EnterpriseISO 27001
EnterpriseGDPR Compliant
GlobalHIPAA
HealthcarePCI DSS
FinanceCCPA
PrivacyFedRAMP
GovernmentCSA STAR
CloudDeployment & Data
Data Residency Options
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