Metaplane was founded in 2019 by Kevin Hu, Guru Mahendran, and Peter Casinelli to bring the rigor of software observability to data. As companies pile more decisions on top of dashboards and machine learning models, silent data failures, a dropped pipeline, a schema change, a sudden null spike, can quietly corrupt downstream reports and erode trust. Metaplane's mission is to catch those failures automatically before stakeholders do.
The platform sits across the modern data stack, connecting to warehouses like Snowflake, BigQuery, Redshift, and Databricks, transformation tools like dbt, and BI tools like Looker and Tableau. It uses machine learning to baseline historical patterns for freshness, volume, distribution, and schema, then raises alerts when metrics drift outside expected bounds. Because the models learn each table's normal behavior, teams avoid the noisy, threshold-heavy alerting that plagues older monitoring approaches.
When something does break, Metaplane's column-level lineage lets engineers trace an anomaly upstream to its source and downstream to every affected report, dramatically shortening incident resolution. The product emphasizes fast time-to-value: teams can connect a warehouse and have automated monitors running within minutes rather than the weeks typical of legacy data quality projects.
Metaplane raised a $13.8 million Series A in March 2024 led by Felicis, with participation from Khosla Ventures, Flybridge, Y Combinator, Stage 2 Capital, B37, and SNR, bringing total funding to roughly $22 million. By that point its customer base had tripled past 100 companies, including data teams at Klaviyo, Ramp, Bose, GoFundMe, and ClickUp, who had collectively run hundreds of millions of data quality checks. The company competes in the fast-growing data observability category alongside Monte Carlo and Bigeye, differentiating on speed of deployment and ML-driven, low-noise anomaly detection.