Decube, an enterprise-focused data trust and context platform, has successfully raised USD 3 million in its latest funding round. The investment is led by Taiwania Hive Ventures, with additional participation from Iterative and 500 Global, marking a significant milestone in the company’s growth journey. This fresh capital comes at a time when enterprises worldwide are intensifying efforts to operationalize artificial intelligence using data they can confidently trust.
With this funding, Decube plans to accelerate its global expansion, strengthen product innovation, and scale rapidly across the Asia-Pacific (APAC) region. As more organizations move beyond AI experimentation, the demand for reliable, production-ready data foundations continues to rise. Consequently, Decube is positioning itself at the center of this transformation.
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As enterprises invest heavily in AI-driven initiatives, many are uncovering a critical challenge. Although modern data platforms, pipelines, and warehouses are in place, organizations often lack a unified way to understand what their data truly represents, where it originates, how it evolves, and whether it can be trusted. As a result, AI systems struggle to deliver consistent, enterprise-grade outcomes.
To address this gap, Decube is building what many enterprises are missing: a context layer for data. In practice, Decube operates between raw data systems and downstream analytics or AI use cases. By doing so, it delivers essential context such as data lineage, ownership, quality indicators, and usage policies without depending on fragmented tools or manual documentation. Therefore, business and data leaders gain a strong foundation that enables AI initiatives to move confidently from pilot stages into full-scale production.
Commenting on the successful funding round, Jatin Solanki, Founder and CEO of Decube said: “Decube was founded on a simple insight: enterprises can’t scale AI without a trusted context layer across their data. This round validates what we are seeing at the heart of almost every large business: enterprises are racing to deploy AI, but most are still missing the context layer that makes AI reliable at an enterprise level. This funding allows us to move faster, expand strategically across APAC, and help our clients turn trusted data into production-grade AI, not experiments. We are building the foundation that lets AI actually work in the real world.”
Looking ahead, Decube intends to deepen its global footprint while focusing strongly on APAC markets, where enterprises are modernizing data estates in preparation for AI at scale. In addition, the company will invest in enhanced platform capabilities, regional partnerships, and large-scale enterprise deployments aligned with rising demand.
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At the core of Decube’s value proposition is its ability to replace fragmented metadata, spreadsheets, and tribal knowledge with a single, unified system of data understanding. As a result, organizations can clearly track data origins, establish accountability, continuously assess data reliability, and provide explainable, trusted inputs to AI and analytics systems. This approach is especially vital for regulated and data-intensive industries, where speed must be balanced with governance and accountability.
Reflecting on the investment, Tawania Hive Co-Founder and Managing Partner Yan Lee said: “We were drawn to Decube because of the clarity of the problem they are solving and the strength of the team executing against it. As AI adoption moves from pilots to core enterprise systems, the need for scalable, production-grade data foundations is becoming non-negotiable. Decube is building a category-defining platform with strong early traction in regulated industries, and we are excited to support the company as it scales across Asia Pacific.”
Currently, Decube supports enterprises across regulated sectors such as banking, financial services, telecommunications, and global corporates. Notably, in Indonesia, PT Superbank, which recently went public, is leveraging Decube as part of its AI foundation to ensure governed, traceable, and production-ready data.
Overall, this momentum reflects a broader shift among Chief Data Officers from isolated governance efforts toward operational data trust embedded directly into everyday data workflows.
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