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BigEye (formerly Toro) scores $17M Series A to automate data quality monitoring – TechCrunch


Bigeye (formerly Toro) scores $17M Series A to automate data quality monitoring
As companies create machine learning models, the operations team needs to ensure the data used for the model is of sufficient quality, a process that can be time consuming. Bigeye (formerly Toro), an early stage startup is helping by automating data quality.
Today the company announced a $17 million Series A led Sequoia Capital with participation from existing investor Costanoa Ventures. That brings the total raised to $21 million with the $4 million seed, the startup raised last May.
When we spoke to Bigeye CEO and co-founder Kyle Kirwan last May, he said the seed round was going to be focussed on hiring a team they are 11 now and building more automation into the product, and he says they have achieved that goal. ....

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Bigeye Raises $17M in Series A Funding


The round was led by Sequoia Capital with participation from existing investor Costanoa Ventures.
The company intends to use the funds to improve the platform and make it available to more data teams.
Now, Bigeye is applying an engineering approach to data, making it effortless for data teams to measure, improve, and communicate data quality for their organizations.
Led by Kyle Kirwan, CEO and co-founder, and by Egor Gryaznov, CTO and co-founder, Bigeye provides a data quality engineering platform that applies proven engineering concepts from DevOps and Site Reliability Engineering (SRE). The solution automatically instruments datasets and pipelines with data quality metrics, creating actionable alerts driven by anomaly detection techniques that enable data teams to prevent incidents from impacting the business. ....

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