Qualytics Data Control Layer

Qualytics Inc. was co-founded by Gorkem Sevinc (CEO) and Eric Simmerman (CTO) and in February 2026 made Atlanta, Georgia its corporate headquarters. It targets Fortune 2000 companies in financial services, insurance, healthcare, supply chain, manufacturing and energy whose data quality programmes depend on thousands of hand-written rules.

The platform applies augmented data quality: it profiles datasets, uses AI to infer quality rules from how data behaves, lets teams add business context and authored checks such as freshness, schema and data diff, and turns results into anomalies, data quality scores and remediation workflows shared by data teams and business users. Positioned as a data control layer, it applies quality signals at the point of use so pipelines, copilots and agents can proceed, flag or stop, with access via MCP, API and AgentQ natural-language governance. It connects to warehouses, databases and lakes including Snowflake, Databricks, BigQuery, Oracle, SAP HANA and Teradata. Customers named include MAPFRE, AES, Brookfield and Wellstar Health System.

• Profiling: Scans datasets to learn structure, distributions and behaviour.
• Inferred checks: AI generates data quality rules automatically from profiled data.
• Authored checks: Freshness, expected schema, data diff and many other rule types.
• Anomalies and scoring: Flags anomalies and computes data quality scores per dataset and field.
• Remediation workflows: Notifications and shared workflows for data teams and business users.
• Control layer for AI: Quality signals via MCP, API and AgentQ natural-language governance.

A Vietnamese insurer can automatically generate quality checks for policy and claims tables instead of maintaining rules by hand. A utility or energy company can monitor meter and asset data feeding operational dashboards. A bank on Databricks can block AI agents from using datasets that fail quality checks.

AI-inferred rules cut the effort of writing and maintaining checks; the vendor cites more than 20,000 rules automated for one customer and 20x ROI in the first year. Business users can resolve anomalies alongside data teams, and the vendor reports 4x faster remediation. Quality signals exposed through MCP and API let AI agents avoid acting on bad data. Native running on Databricks suits lakehouse users.

Analysts describe augmented data quality, where machine learning infers rules, as a fast-growing replacement for manual rule libraries. As banks, insurers and manufacturers in Southeast Asia deploy copilots and agents, they need controls that stop AI from acting on incomplete or wrong data.

Qualytics Inc. made Atlanta its corporate headquarters in February 2026, opening an office at Atlanta Tech Village. It raised a USD 10 million Series A in June 2025 after 5x revenue growth. Backers include BMW i Ventures, Conductive Ventures, SaaS Ventures, Inner Loop Capital and The LegalTech Fund. It is a Databricks technology partner since January 2026.