Restricted data
Sensitive or regulated data cannot reach AI safely. Compliance constraints keep it out of training, validation, and inference.
Company
About CUBIG
CUBIG builds the operating layer for AI-ready execution, turning restricted, unusable, and unstable enterprise data into states AI can actually run on.
Category
What is AI-ready execution?
AI-ready execution is the operating layer that makes enterprise data usable, reliable, and stable for production AI.
Most enterprises have data, but most of it is not ready for AI. Some is restricted and cannot reach AI safely. Some exists but is unusable because of missing values, bias, or coverage gaps. And AI that works in a PoC often drifts in production once schemas, pipelines, and conditions change, so results can no longer be reproduced.
CUBIG builds the operating layer that closes these gaps. Two market entry paths, one long-term platform destination: Syntitan. Path A serves AI-ready data demand through Syntitan and DTS. Path B serves sensitive AI workflow enablement through LLM Capsule. Both converge into Syntitan.
Mission
Why we exist.
Enterprise AI stalls because data is restricted, unusable, or because execution becomes unstable in production.
What we believe
Most teams can make AI work in a PoC. Production is a different problem, and the cause is rarely the model or the compute. It is the state of the data underneath every run, where work usually stops before it ever reaches production.
We believe these three problems, not models or compute, are what keep enterprise AI out of production. CUBIG builds the operating layer that resolves all three.
What we do
Make data usable, reliable,
Make data usable, reliable,
and stable for production AI.
Unusable data
Data exists but is not usable: missing values, bias, coverage gaps, restricted access. The PoC works. Production does not.
Unstable execution
After deployment, data and execution conditions change, so results cannot be reproduced. Traceability disappears and root cause becomes impossible.
We make enterprise data usable by rebuilding restricted and scarce data into AI-ready states, and stable in production by fixing the data state behind every AI run and keeping results reproducible.
That is what turns a PoC into production.
Story
How we got here.
CUBIG was founded in 2021 by a team that had spent years building enterprise AI in regulated industries: finance, healthcare, defense. We kept hitting the same three walls: data we could not use because of compliance, data that existed but was too damaged for training, and AI that worked in a PoC but degraded in production after deployment.
We looked at existing tools. Data governance managed access but did not make data usable. MLOps tracked models but not the data state behind each run. None were designed to work together as one layer. The problem was not any single tool. It was the absence of a layer that handled all three blockers at once.
So we built what was missing: Syntitan, the platform that makes enterprise data AI-ready and keeps every AI run reproducible in production. Its capabilities carry the work. DTS rebuilds locked, scarce, or regulated data into AI-ready states, and LLM Capsule runs LLM and agent workflows on sensitive data without exposing the raw enterprise data. Together, inside one platform, they resolve restricted, unusable, and unstable data: the three conditions that keep enterprise AI out of production.
At a glance
Where we are today.
2021
Founded
Seongnam, Korea · Belfast, UK
AWS
Marketplace partner
LLM Capsule on AWS Marketplace
2
Global entities
CUBIG Corp (KR) · CUBIG Ltd (UK)
Team
The people building it.
Our team comes from enterprise AI, data engineering, and privacy technology. We have built and broken AI systems at scale, which is why we know exactly where production AI fails.
CUBIG Team
AI infrastructure engineers
Practitioners who have operated AI in regulated enterprise environments: finance, healthcare, manufacturing. Every product decision comes from something we had to fix ourselves.
Research & Privacy
Data reconstruction specialists
The research team behind the DTS engine and the field-handling layer inside LLM Capsule. Measured guarantees, not policy promises.
Enterprise Engineering
Platform & integration
Responsible for Syntitan: Release State, Run Binding, and the integration layer that connects to existing ML pipelines, data platforms, and runtime environments.
Platform & capabilities
The structure that makes data AI-ready.
Syntitan is the long-term platform. DTS and LLM Capsule are core capabilities that converge into it, not standalone products beside it.
Platform
Syntitan
The AI-Ready Data Platform. Diagnose data readiness, prepare it for use, fix the data state as a Release State, and bind every AI or agent run to it so results stay reproducible.
More →Capability
DTS
AI-ready data transformation engine. Rebuilds locked, scarce, or regulated data into AI-ready states, expands coverage, and restores data utility. Works within Syntitan and on its own.
More →Capability
LLM Capsule
Context-preserving data layer for AI. Runs LLM, RAG, and agent workflows on sensitive data without exposing the raw enterprise data. Structure-preserving substitution with business-ready reconstruction.
More →
Partners
Trusted by enterprise
Trusted by enterprise
and government.
From global cloud and research partners to major Korean financial institutions and national defense, CUBIG operates where the data stakes are highest.
Technology & Cloud
Finance & Enterprise
Defense & Public sector
Values
How we work.
01
A layer, not features
We build the layer everything else runs on. Features solve single problems. A layer solves a class of problems in sequence and becomes load-bearing for the AI above it. Every decision starts with which problem it solves and what it makes possible next.
02
Production is the only test
A PoC is not proof. We build for production: restricted data, compliance constraints, schema changes, multi-team pipelines. Every decision is tested against one question: does it hold when conditions change after deployment?
03
Evidence over assertion
Every claim is backed by operational evidence: before and after outcomes, state comparisons, reproducible runs. We do not say "improves accuracy" without showing what changed and how it can be verified. If we cannot prove it, we do not say it.
Contact
Get in touch.
Enterprise & Architecture
Talk to an architect
Map your production constraints (restricted, unusable, or unstable data) to the right path across Syntitan, DTS, and LLM Capsule.
Talk to an architect →General inquiries
Press, partnerships, research
Research collaboration, press, partnership discussions, or anything not covered above.
[email protected]Korea headquarters
CUBIG Corp
4F, NAVER 1784, 95 Jeongjail-ro, Bundang-gu, Seongnam-si, Gyeonggi-do, Republic of Korea.
United Kingdom
CUBIG Ltd
21 Arthur Street, Belfast, Antrim, BT1 4GA, United Kingdom.
Make your AI runs
reproducible in production.
Start with Syntitan, and bring in DTS and LLM Capsule where you need them.