Toro provides automated data-quality monitoring that detects anomalies and alerts data teams when values fall outside normal thresholds. The product is designed to surface problems in data content—such as mislabeled fields or out-of-range figures—before they propagate into dashboards and ML models. The founders built their approach based on tools and experience from working on Uber’s data team. Toro has operated for just over a year and is keeping the team lean, with four employees including the two co-founders. The company plans to add a couple of data scientists in the coming year as it continues to build out the product. Financially, Toro recently closed a seed round to support its growth efforts.

Total raised

$4M

Funding rounds

1

Latest round

Seed

Latest activity

May 2020