Qualytics, developer of AI-powered tools to ensure data quality for AI models, closed a $10 million Series A funding round. The round was led by BMW i Ventures, with participation from Conductive Ventures, Firebrand Ventures, Tech Square Ventures, Knoll Ventures, SaaS Venture Capital, Inner Loop Capital, and Rich Family Ventures.
"With this new investment and our strong revenue growth, we’re more confident than ever that Qualytics is delivering what modern data practitioners need to manage data quality at scale," commented Gorkem Sevinc, Co-founder and Chief Executive at Qualytics.
Qualytics' platform proactively manages data quality through intelligent rule generation, automated anomaly detection, and no-code workflows. The platform addresses the increasing need for reliable data in AI-driven operations, a challenge exacerbated by the volume of data used in modern AI systems. The company's technology automates data quality rules, improving data resilience at scale. This contrasts with legacy systems that rely heavily on manual rule creation.
A number of companies offer data quality solutions, including Talend, which provides a comprehensive data integration and quality platform, and Informatica, known for its broad range of data management tools.
Gartner projects that 70% of organizations will automate data quality by 2027, highlighting the growing market need. Qualytics has already secured a major financial services client among its customer base and integrated its platform with various big data platforms and data catalog tools, including Databricks, Snowflake, SQL Server, Oracle databases, Atlan, and Alation.
The funding will support scaling the product and go-to-market teams to expand platform capabilities, onboard new customers, and boost sales.
