Quest Software Releases Quest Data Modeler and Quest Data Intelligence
Quest Software said it released new capabilities for the Quest Trusted Data Management Platform, adding cloud-native data modeling and AI-powered data intelligence. The update targets how organizations manage governed data across modeling and policy, with an expanded library of QuestAI assistants.
Quest described fragmentation across data modeling tools, governance suites, and AI assistants as a source of inconsistent naming, broken audit trails, and assistants running on ungoverned data. The company said the platform now supports governance and lineage alongside how data is modeled, aiming to keep standards consistent across the platform and shared across consumption.
Quest Data Modeler is described as a cloud-native tool that combines AI-assisted modeling with enterprise-level governance in a single offering. It includes AI-Assisted Modeling via a natural-language interface, Real-Time Collaborative Modeling in a single live workspace, an Enterprise Model Repository with model locking and version history, Full-Stack Modeling across conceptual, logical, and physical layers, and erwin Heritage and Hybrid Coexistence to migrate assets and maintain hybrid workflows.
Quest Data Intelligence expands QuestAI assistant capabilities and adds AI-Powered Policy Manager, Universal Semantic Assistant, and an Expanded QuestAI Assistant Library. AI-Powered Policy Manager generates policies from EU AI Act, NIST AI Risk Management Framework, and GDPR and enforces them at the point of data access with continuous compliance monitoring and full audit trails. The company’s expanded assistant library is said to cover glossary and ownership, data lineage, compliance, data products, and data quality.
“Trusted data is the backbone of any modern AI strategy, and our continued innovation is helping organizations turn AI ambition into real business value – with lower risk, higher accuracy, and the trusted data that makes faster AI deployment possible,” said Michael Laudon, Chief Product and Technology Officer, Quest Software. “At the pace we’re all moving in the AI era, trust can’t be tacked on after the fact – it has to be baked in from the start, or AI initiatives stall. That’s why we designed the Quest Trusted Data Management Platform with multiple entry points, each aligned to different stages of enterprise data and AI maturity, so we can meet our customers where they are.”
“The bottom line is, there is no trusted AI without trusted data, and there is no trusted data without sound data modeling. That is where it all begins,” said Rocky Creel, Executive Director, JP Morgan Chase. “Fragmented data landscapes, inconsistent definitions, and manual processes slow everything down and erode confidence in what we deliver downstream.”
Quest said its new releases built on the Automated Data Product Factory capability introduced earlier this year, and it described Quest Data Intelligence and Quest Data Modeler working jointly within the Quest Trusted Data Management Platform.