2026 data Voucher

You have data, why is it hard to use for AI?

Many companies have data but cannot turn it into use. The problem is not "lack of data" but "data not ready for AI".
CUBIG provides the infrastructure layer that makes data AI-ready. We diagnose enterprise data against AI-Ready criteria and convert it into usable data structures.

Voucher inquiry

What is the Data Voucher program?

The Data Voucher program is a government-funded scheme that helps companies secure or generate data and build environments ready for AI and analytics use.

CUBIG is an official Data Voucher supplier that meets the security and compliance requirements for AI use. We cover the full process — from diagnosis through transformation and validation.

Dataset K-Data Buyer Demand CUBIG Supplier K-Data

K-Data NIA

3-party agreement model

Across every industry, CUBIG handles any data

Mobility & Logistics
Manufacturing
Finance & Insurance
Retail & Commerce
Marketing & Ads
Energy & Environment
Public Sector
Healthcare
EdTech
Media & Content
Mobility & Logistics
Manufacturing
Finance & Insurance
Retail & Commerce
Marketing & Ads
Energy & Environment
Public Sector
Healthcare
EdTech
Media & Content

Recommended for

The Data Voucher fits these kinds of companies

Companies that need data sharing

Plenty of internal data, but external sharing or reuse is blocked

Companies handling sensitive data

When personal, financial, or medical data is restricted by regulation

Companies adopting AI

When data is missing or low quality

Process

The Data Voucher works in five steps

1
Issue eligibility

Verify Data Voucher eligibility
2
Pre-consultation

Pre-review of data feasibility
3
Submit documents

Detail the project and apply
4
Tripartite agreement

Agreement with applicant, CUBIG, and NIA
5
Execution

Run the work and deliver results

Voucher supply

Synthetic data generation for open and shared public data — DTS

Secure by design

Generate synthetic data without touching the source

Any data type

Convert text, tables, images and more

Same fidelity as source

High-fidelity synthetic data ready for training and analytics

Flexible deployment

Cloud / on-prem / API options to fit your security and infra

Already validated

Backed by 1,500+ AI model training projects and PoCs

Use cases

In every industry that needs data, we are building real-world cases

Enterprise Shadow AI risk - digital shield protecting sensitive data flowing into AI models with tokenization control layer

Verified in the field

Already used by a wide range of companies

Anomalies and edge cases matter but are too rare to train on. With DTS we could expand data while keeping the normal/anomaly structure, and validate risk scenarios repeatedly without touching sensitive information. Model validation and decision speed improved noticeably.

Financial firm A Risk management team, Kim

Collecting data for specific conditions in the field is expensive and often impossible. After adopting DTS, we built data environments first, ran simulations, and then clarified our real collection strategy. Escaping the wait-for-data trap was the biggest change.

Manufacturer B DX team, Han

Analysis on real citizen data was always limited by privacy. After DTS, we could validate policy scenarios and data usefulness without touching source data — especially filling gaps in missing or skewed segments helped us standardize our analysis baseline.