Decube Launches Trusty AI Data Assistant for Enterprise Metadata

Singapore-based Decube has launched Trusty AI, an artificial intelligence assistant designed to let enterprise teams query their data metadata using natural language. The product arrives as part of Decube's broader Data Trust platform, targeting organizations struggling with metadata scattered across catalogs, observability tools, and governance systems.

The announcement follows a US$3 million funding round that Decube said will support global growth and expansion across Asia Pacific. The company already works with businesses in tightly regulated fields, including regional banks and financial institutions. In Indonesia, Decube named PT Superbank, an Indonesian digital bank, as a customer.

Trusty AI draws on lineage graphs and data quality monitors to answer questions about data dependencies, incidents, and sensitive data flows. According to Tech in Asia's coverage, the tool positions itself as a data context platform rather than just another metadata catalog.

Here's what that actually means for the person clicking through dashboards at 2 a.m. when a pipeline breaks: instead of manually tracing which table feeds which report, you can ask the system what changed upstream. The interface handles the lineage traversal (a problem that has plagued users for years, frankly).

Decube's official documentation reveals additional capabilities beyond the AI assistant. The platform offers column-level lineage mapping, automated policy management for data governance, and ML-powered anomaly detection. Users can configure data quality tests without writing code, though custom SQL testing remains available for specific business requirements.

The company's product page details features like Text2SQL conversion, automated data quality suggestions, and integration with communication platforms such as MS Teams or Slack for instant failure alerts. The physical reality of using this means fewer tabs open, fewer manual lookups, and alerts that actually land in your notification stream rather than some forgotten dashboard.

This launch fits a wider shift in enterprise software where context around data is becoming a foundation for responsible AI in live systems. That demand comes from regulation and day-to-day risk. Banking rules such as BCBS 239, a global standard for risk data aggregation and reporting, call for the sort of traceability that column-level lineage can offer.

A growing group of startups is also building tools for cataloging, lineage, and governance. That list includes DataHub, an open-source metadata platform, and Secoda, a data catalog and governance software company. The available sources do not label them as Decube competitors or describe a direct contest with Decube.

Decube said many companies still lack one place that explains what their data means and where it starts. They also need to track how the data changes and whether it is reliable for AI use. The Data Trust platform is built to supply that context by surfacing lineage, ownership, quality, and usage rules without manual documentation or scattered tools.

Whether enterprises actually pay for another layer in their data stack remains the real question. The market is crowded, the problem is real, and the difference between a tool that gets adopted and one that collects dust often comes down to whether it saves engineers enough time to justify the cost.

Artūras Malašauskas is an AI Systems Integrator with 20+ years of production-grade web engineering experience. He has designed, shipped, and scaled enterprise Python/PHP systems for logistics, SaaS, and public-sector clients. For the past year, he has focused exclusively on AI integrations: deploying open-source LLMs, building generative media pipelines (image, audio, video), and engineering multi-agent workflows for real production environments. His standard: reproducibility, security, cost-efficient inference—no vaporware. He documents and evaluates emerging AI tooling, separating verified capabilities from marketing noise. Technical editor at: muza-ai.eu, ai-verslas.lt, ai-naujinos.lt Connect on LinkedIn