Decube Secures $3M to Build the Data Foundations Enterprises Need for AI

As AI spending accelerates across Asia Pacific, the Malaysian startup is betting that context — not more models — is what enterprises are missing

Malaysia-based Decube has secured US$3 million in a fresh funding round led by Taiwania Hive Ventures, with backing from Iterative and 500 Global, taking its total capital raised to US$5 million.

The company said the fresh capital will be used to support global expansion, accelerate product development, and deepen its presence across the Asia Pacific region, where enterprises are increasingly preparing their data foundations for large-scale AI deployment.

While enterprises across Asia Pacific are investing heavily in AI tools, many are encountering the same problem: AI systems struggle to deliver reliable outcomes when the data feeding them lacks clarity, ownership, and traceability.

Decube positions itself in this gap. Its platform sits between raw data systems and AI or analytics tools, acting as a context layer that explains what data means, where it comes from, how it changes, and whether it can be trusted.

Rather than focusing on model performance, Decube addresses a more basic question enterprises are now asking: Is our data actually ready for AI?

From experimentation to production

Many companies have modern data warehouses, pipelines, and dashboards. However, moving AI from pilot projects into real-world use often exposes missing foundations, such as:

• unclear data ownership and accountability
• limited visibility into data lineage and transformation
• inconsistent data quality and usage rules

Decube’s platform automatically tracks these elements without relying on manual documentation or disconnected governance tools. By unifying data understanding in one system, enterprises can assess whether data is suitable before it powers AI models or analytics workflows.

This capability becomes increasingly important as AI systems are embedded into core business decisions rather than isolated experiments.

APAC focus reflects enterprise reality

Decube said demand is strongest in Asia Pacific, where enterprises are modernising legacy data environments while facing rising regulatory and governance expectations.

Founder and chief executive Jatin Solanki said many organisations are moving quickly to adopt AI without the context required to make it dependable at scale.

“Decube was founded on a simple insight: enterprises can’t scale AI without a trusted context layer across their data,” Solanki said. “Companies are racing to deploy AI, but most are still missing the foundations that make it reliable in production.”

He added that the latest funding will allow the company to expand more strategically across the region and help enterprises move beyond AI experimentation.

Traction in regulated industries

Decube said its platform is already being adopted by enterprises in highly regulated and data-intensive sectors, including banking, financial services, telecommunications, and large corporates.

In Indonesia, PT Superbank has adopted Decube’s platform as part of its AI stack to ensure the data used in analytics and AI applications is properly governed and traceable. The move reflects a wider change among data leaders, who are increasingly integrating data trust into day-to-day operations rather than managing governance as a standalone function.

For investors, the appeal lies in Decube’s focus on a problem that grows more urgent as AI adoption matures.

Taiwania Hive Ventures co-founder and managing partner Will Wang Yan Lee said enterprises are increasingly realising that AI performance depends on the quality and clarity of underlying data.

“As AI moves from pilots to core enterprise systems, the need for production-grade data foundations is becoming non-negotiable,” he said, adding that Decube is building a platform designed for this next phase of AI adoption.

Looking ahead

With US$5 million raised to date, Decube is now focused on expanding its product capabilities, strengthening regional partnerships, and supporting more enterprise deployments across Asia Pacific and beyond.

As enterprises spend more on AI, the market is beginning to separate experimentation from execution. Decube’s bet is that the next wave of enterprise AI spending will shift away from new models and toward the less visible — but essential — infrastructure that makes AI trustworthy, explainable, and usable at scale.

Whether that thesis plays out will depend on how quickly enterprises prioritise data context as a core requirement, rather than an afterthought, in their AI strategies.

Quick Takeaways

• Decube raised US$3 million in a funding round led by Taiwania Hive Ventures, with participation from Iterative and 500 Global, bringing its total funding to US$5 million.
• The startup builds a data context and trust layer that sits between enterprise data systems and AI, helping organisations understand, govern, and validate data before it is used.
• Demand is rising as enterprises across Asia Pacific move from AI pilots to production, exposing gaps in data readiness and governance.
• Decube is gaining early traction in regulated and data-intensive sectors such as banking and financial services.
• The funding will support product development, regional expansion, and enterprise deployments, particularly across APAC.