You ever wonder why everyone wants AI to be smarter, faster, more “transformative,” but no one talks about what happens when that shiny new model is trained on garbage data? It’s like feeding Kobe beef to a vending machine and being surprised it spits out a warm can of Diet Mistake. That’s where Qualytics steps in, quietly, precisely, with the confidence of a company that doesn’t need to shout. Because when your platform surfaces 30,000+ real-world anomalies a month before they turn into six-figure clean-up jobs, your customers do the talking for you.
On June 23, 2025, Qualytics locked in a $10M Series A, oversubscribed and led by the sharp operators at BMW i Ventures, with Conductive Ventures and The Hill Fund by Firebrand Ventures riding shotgun. Returning believers like Tech Square Ventures, Knoll Ventures, Inner Loop Capital, SaaS Venture Capital, and Rich Family Ventures doubled down. Why? Because this isn’t a trend. It’s a correction.
Co-founders Gorkem Sevinc (CEO) and Eric Simmerman (CTO) weren’t guessing when they built this. These guys have been in the trenches, Sevinc with Johns Hopkins, Facet Wealth, and miDiagnostics, Simmerman across Interos, Social Tables, HealthPrize, and FolderGrid. They didn’t whiteboard a theory, they lived the pain of “legacy” tools that couldn’t scale, couldn’t adapt, and definitely couldn’t keep up with a world moving at machine learning speed.
Let’s be clear, Qualytics isn’t a dashboard you check when the lights blink red. It’s AI-native data quality infrastructure that works while you sleep. Proactive anomaly detection. Intelligent rule generation. No-code workflows for people who don’t want to file a Jira ticket just to monitor revenue-impacting data. And because it’s built on Apache Spark, it plays nice with your stack, Databricks, Snowflake, Oracle, SQL Server, Atlan, Alation, no forklift upgrades required.
Regulated industries? Financial services just signed one of the top three U.S. institutions. Healthcare and supply chain are next. Why? Because you can’t build AI on lies, and Qualytics makes sure your data doesn’t whisper sweet nothings to your models. This is about trust. At scale.
