Enterprise AI adoption is moving fast and organisations are hitting an unexpected wall where AI systems do not actually understand their data. Decube, which recently raised US$3 million in funding, is tackling this problem head-on with the launch of Trusty AI, a Data Context Platform capability designed to let teams ask simple questions about their data ecosystems using natural language.
While enterprises generate vast metadata across catalogues, lineage tools, observability platforms, and governance systems, accessing that knowledge in real-time remains difficult. Teams still spend hours manually tracing dependencies when data incidents strike or when executives demand answers on reliability.
Trusty AI synthesises metadata across lineage graphs, quality monitors, and operational signals to deliver instant answers. Instead of navigating dashboards, simplifying the process of retrieving answers. Users are able to ask interactive questions including Which dashboards depend on this dataset? Where is sensitive data flowing? Are there incidents affecting this warehouse?.
“Enterprises already generate enormous amounts of metadata describing their data assets but accessing that knowledge quickly remains difficult,” said Jatin Solanki, CEO & Founder of Decube. “We believe the next generation of enterprise data platforms will be defined by Data Context Platforms—systems that transform fragmented metadata into real-time intelligence. By providing instant, context-rich answers about data, Trusty AI enables teams to move faster, reduce risk, and build greater confidence in AI-driven decisions.”
As organisations move from AI pilots to production, that context layer is becoming less optional and more essential as AI systems are only as effective as the context provided to them.
Trusty AI is now available as part of Decube’s Data Trust platform.
Entelechy Asia 