Anomalo is a data quality and observability platform founded in 2018 by Elliot Shmukler (CEO) and Jeremy Stanley (CTO), who previously worked together at Instacart on data quality challenges. The company is headquartered in the San Francisco Bay Area and positions itself as the autonomous data system for the agentic enterprise.
The product applies machine learning to automatically monitor structured and increasingly unstructured data, detect anomalies, investigate root causes, and surface reports for data and analytics teams. Unlike rules-based testing frameworks (e.g., dbt tests, Great Expectations), Anomalo learns expected data patterns and flags deviations without requiring engineers to author rules for every column or table. Recent product investment has focused on agentic monitoring and unstructured data quality for generative AI and RAG pipelines.
Anomalo raised a $33M Series B in January 2024 led by SignalFire, with strategic investment from Databricks Ventures and continued support from existing investors Norwest Venture Partners, Two Sigma Ventures, and Foundation Capital. Total funding stands at approximately $72M. In late 2024 the company also announced strategic follow-on funding to expand unstructured monitoring capabilities. Reported growth includes 177% YoY ARR growth in fiscal Q3 2023 and more than 15x ARR growth since the Series A.
Typical customers are mid-market and enterprise data teams running modern data stacks on Snowflake, Databricks, BigQuery, and similar warehouses. Anomalo competes with Monte Carlo, Bigeye, Acceldata, Soda, and Datadog in the broader data observability category, differentiating on ML-driven autonomous monitoring and unstructured data coverage.
Buyers should evaluate Anomalo against rules-based alternatives if their data is small and stable, versus ML-driven platforms if they have many tables and limited engineering bandwidth to maintain explicit tests. Strengths include depth on warehouse-native monitoring and a strong founding team; trade-offs include premium positioning and the need to grant warehouse access for monitoring queries.