How Validio is Fixing Enterprise Data Quality for the AI Era

Validio, the agentic enterprise data management platform, led by Patrik Liu Tran, Adrian Strömberg, Sophia Granfors, and Christopher Alfred Brown, has raised $30 million in Series A funding led by Plural. Previous investors and angels such as Lakestar, J12, Kevin Ryan (MongoDB), Denise Persson (Snowflake), and Emil Eifrem (Neo4J) also participated in the round. The round brings Validio’s total funding to $47 million and will be used to further scale go-to-market across the US and Europe and continue development of its agentic data management platform.

The shift from “garbage in, garbage out” to “garbage in, disaster out” reflects growing concerns around poor data quality in AI systems. Research from Gartner identifies data quality and availability as the leading barrier to AI adoption, while a study by Massachusetts Institute of Technology found that about 95% of AI projects fail to reach production. In banking, regulations such as BCBS 239 have required high-quality reporting data for over a decade, yet compliance remains limited.

Traditional data management tools, often dependent on manual and rules-based systems, struggle to keep pace with AI-driven operations due to slow deployment and high maintenance demands. To address this challenge, Validio provides data quality and observability solutions used by organizations such as Nordea, Canva, Deutsche Glasfaser, Truecaller, Surfshark, Walden, and AllianceBernstein to ensure reliable and high-quality enterprise data.

Patrik Liu Tran, CEO and founder of Validio, highlighted that many enterprises still struggle to trust their data for reporting and analytics, making AI adoption even more challenging. In the AI era, poor data quality can escalate from “garbage in, garbage out” to “garbage in, disaster out,” contributing to the high failure rate of AI initiatives. Validio’s platform focuses on helping organizations build reliable data foundations with curated, quality-assured data while expanding globally with support from Plural.

Before founding Validio in 2019, CEO Patrik Liu Tran advised global enterprises on AI and data strategy, frequently observing how poor data quality prevented AI initiatives from reaching production. Ensuring reliable data at scale requires enterprise-grade platforms rather than fragmented monitoring or internal tools.

Validio’s agentic platform autonomously detects and resolves data quality issues across billions of records, replacing thousands of manual rules with automated monitoring, anomaly detection, and data lineage capabilities. Organizations report significantly faster issue detection and up to a 95% reduction in manual investigation time, while complex data lineage setups that once took months can now be deployed in a single day.

Driven by rising demand for trusted enterprise data and AI readiness, Validio has increased annual recurring revenue by 800% over the past 12 months, helping organizations strengthen analytics, meet regulatory requirements, and unlock the full potential of AI.

Pierre-Dimitri Gore-Coty, partner at Plural, noted that poor data quality continues to prevent many large enterprises from turning AI ambitions into production systems. The platform developed by Validio is positioned as a leading solution for enterprise data reliability, with expectations of supporting global expansion and strengthening its role in enterprise data management.

Denise Persson highlighted that data quality has become mission-critical for AI success, noting that Validio addresses the data trust challenge with an AI-powered platform for data quality and lineage across enterprise, AI, and agentic workloads while expanding globally.

Kevin Ryan, founder of MongoDB and investor in Validio, emphasized that bridging the gap between AI ambition and execution depends on trusted data. Validio’s platform addresses this challenge at enterprise scale, supporting continued growth.