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Anomalo Data Quality

Anomalo is an autonomous data system that monitors, investigates, surfaces, and reports on data using Agentic AI.

Venture Funded$24MSeries AAmplify PartnersFirst Round CapitalVillage Global

data qualityanomaly detectiondata monitoringdata governance

About

The vendor describes Anomalo as an autonomous data system for the agentic enterprise, enabling "Self-Driving Data." It uses Agentic AI to autonomously monitor, investigate, surface, and report on data without requiring code, prompts, or manual effort. The system includes nine agents, each handling a distinct class of data work. These agents include the Table Observability Agent for monitoring data availability, freshness, and schema consistency; the Data Quality Agent for defining and monitoring data quality; the Data Insights Agent for proactively identifying noteworthy changes and delivering reports; and the Conversational Analytics Agent (AIDA) for natural language data analysis and report composition. Coming soon agents include Data Issue First Responder, Dashboarding & Reporting, Business KPI Monitoring, and Experiment Evaluation. The vendor states Anomalo is "enterprise-grade" and offers flexible deployment options, including in a VPC or as SaaS, and integrates with various data platforms and identity providers like Okta, Google, and Microsoft Entra ID through SAML-based SSO. It is also stated to be SOC 2 Type II, GDPR, and HIPPA compliant.

Read from anomalo.com on 2026-08-26. We describe what the vendor states; we do not audit it.

Enterprise Readiness

from cataloged data

55/100 · Established

Security & ComplianceNot disclosed

No compliance certifications listed

Deployment FlexibilityPartial

Cloud-based: Cloud

Integration DepthStrong

8 documented integrations

Proven AdoptionPartial

6 documented use cases

Company MaturityStrong

Founded 2018 · Series A

Composite of public compliance, deployment, integration, adoption, and company signals. “Not disclosed” reflects gaps in available data, not a vendor deficiency.

Enterprise Use Cases

Automated data anomaly detection

Real-time data quality monitoring

Data pipeline reliability assurance

Compliance and governance reporting

Root cause analysis for data issues

Scalable enterprise data observability

Integrations

SnowflakeBigQueryRedshiftDatabricksLookerTableauFivetranAirflow

How Anomalo Data Quality compares

Tool	Readiness	Pricing	Deployment	Compliance	Integrations
Anomalo Data Quality	55 · Established	Enterprise	Cloud	—	8
Stemma AI Catalog	Not scored	Enterprise	Cloud, On-Premise, Hybrid	—	8
Marquez Data Lineage	Not scored	Open Source	Cloud, On-Premise, Hybrid, Self-Hosted	—	8
ThoughtSpot	62 · Established	Paid	Cloud, Self-Hosted	—	5

Peers from the same category, ranked by Enterprise Readiness. Readiness is a composite of cataloged compliance, deployment, integration, adoption, and company signals.

Frequently Asked Questions

What is Anomalo Data Quality used for?

Anomalo Data Quality is anomalo is an autonomous data system that monitors, investigates, surfaces, and reports on data using Agentic AI. It is commonly used for automated data anomaly detection, real-time data quality monitoring, data pipeline reliability assurance, and compliance and governance reporting.

Is Anomalo Data Quality free, and how is it priced?

Anomalo Data Quality uses enterprise pricing, typically a custom quote based on seats, usage, and requirements. Contact the vendor for a quote.

How can Anomalo Data Quality be deployed?

Anomalo Data Quality supports Cloud deployment. It is delivered as a cloud-hosted service.

What does Anomalo Data Quality integrate with?

Anomalo Data Quality documents 8 integrations, including Snowflake, BigQuery, Redshift, Databricks, Looker, and Tableau.

When was Anomalo Data Quality founded?

Anomalo Data Quality was founded in 2018 and has raised $24M in funding.

Is Anomalo Data Quality enterprise-ready?

Based on cataloged data, Anomalo Data Quality has an Enterprise Readiness score of 55/100 (Established tier), derived from its compliance, deployment, integration, adoption, and company-maturity signals.

Quick Facts

PricingEnterprise

DeploymentCloud

Founded2018

Funding$24M

CategoryAnalytics & BI

Procurement

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