Anomalo AI Data Quality Platform

Anomalo, Inc. is a data quality company based in Palo Alto, California, co-founded by Elliot Shmukler (CEO) and Jeremy Stanley (Chief Scientist), who worked together at Instacart and saw how often data quality broke down at scale. It replaces large sets of hand-written data rules with machine learning that learns what normal data looks like and flags problems automatically.

The platform monitors tables in warehouses and lakehouses with unsupervised anomaly detection, validation rules, observability checks, automated lineage and root-cause analysis. Anomalo Unstructured uses generative AI to score documents and transcripts for quality issues before they feed AI applications, and newer agents add data documentation, data insights and AIDA, a conversational analyst. It can run as SaaS or fully inside the customer's VPC. Customers named on the site include Discover, Equifax, Nationwide, ADP, Block, Atlassian and Notion.

• Anomaly detection: Unsupervised machine learning flags unexpected changes in table data.
• Data validation: Rule-based checks complement ML monitoring for known requirements.
• Table observability: Monitors freshness, volume and schema changes across warehouses.
• Root cause and lineage: Automated lineage and investigation show where issues start and what they affect.
• Unstructured data monitoring: Generative AI scores documents for custom quality issues before AI use.
• AIDA and agents: Conversational analyst plus agents for documentation and data insights.

A Vietnamese bank can monitor credit and transaction tables for anomalies before risk models and regulatory reports run. An insurer can check claim documents and call transcripts for quality before using them in a generative AI assistant. An e-commerce platform can detect broken marketing and order data feeds early.

ML-based monitoring finds issues that rigid rules miss; the vendor cites a financial services customer whose legacy system needed more than 3,000 manual rules. Deployment inside the customer's own VPC with a choice of LLM keeps sensitive data in place. Quality checks for unstructured documents reduce the risk of feeding poor content to generative AI. The platform lists SOC 2 Type II, GDPR and HIPAA compliance.

As enterprises put more data into analytics and generative AI, data quality failures become costly and hard to catch with manual rules. Banks, insurers and e-commerce firms in Southeast Asia running Snowflake, Databricks or BigQuery are adopting automated data quality monitoring to support AI and regulatory reporting.

Anomalo, Inc. lists its address at 855 El Camino Real, Palo Alto, California. Investors include SignalFire, Norwest, Foundation Capital, First Round Capital, Databricks Ventures, Snowflake Ventures (2025) and Smith Point Capital (USD 10 million Series B extension, November 2024). It was included in the 2025 Gartner Magic Quadrant for Data Quality and is available on AWS Marketplace.