Decube, a Malaysia-based data trust and context platform for enterprise artificial intelligence (AI), has raised $3 million in its latest funding round, which is being led by Taiwania Hive Ventures, with participation from Iterative and 500 Global.

The firm said in a statement on Wednesday that the funding will support its global growth, continued product innovation, and rapid expansion across the Asia Pacific (APAC) region, as enterprises increasingly look to operationalize AI on top of data they can trust.

With this funding, Decube plans to deepen its global footprint while expanding rapidly across the APAC region, where enterprises are modernizing data estates and preparing for AI at scale.

The company will invest in product capabilities, regional partnerships, and enterprise deployments aligned with this growing demand.

“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,” said Jatin Solanki, Founder and Chief Executive Officer of Decube.

It is noted as organizations invest heavily in AI, many are discovering a hard truth: AI systems are only as effective as the context provided to them.

While enterprises have modern data platforms, warehouses, and pipelines, they often lack a unified way to explain what their data actually means, where it comes from, how it changes, and whether it should be trusted.

Decube said the firm is building what many enterprises are missing: a context layer for data.

In practical terms, it said the firm sits between raw data systems and AI or analytics use cases, providing the critical context required for responsible and scalable decision-making.

This includes understanding lineage, ownership, quality, and usage policies—without relying on manual documentation or disconnected tools.

For business and data leaders, this context layer becomes the foundation that allows AI initiatives to move from experimentation to production with confidence.

Decube’s platform helps enterprises move beyond fragmented metadata, spreadsheets, and tribal knowledge by unifying data understanding into a single system.

This enables organizations to know where data originates and how it is transformed; establish accountability and ownership across data assets; continuously assess data reliability before it is consumed; provide trusted, explainable inputs to analytics and AI systems.

This approach is increasingly critical for regulated and data-intensive industries, where AI adoption must balance speed, trust, and accountability, said the firm.

“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,” Tawania Hive Co-Founder and Managing Partner Will Wang Yan Lee said.

It is noted that Decube is already supporting enterprises across highly regulated industries including regional banks, financial institutions, telcos, and global corporates.

In Indonesia, PT Superbank, which recently went public, is using Decube as part of its AI foundation to ensure that the data powering analytics and AI is governed, traceable, and ready for production use.

This reflects a broader shift among Chief Data Officers: moving from isolated governance initiatives toward operational data trust embedded directly into data workflows.

Hong Leong expects continued upbeat AI spending to underpin robust tech sector in Malaysia this year