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Group company

Origin Big Data — the semantic layer specialists.

Driven by ontology engineering, Origin Big Data bridges the business-data semantic gap to build enterprise semantic intelligence infrastructure for enterprises running AI at scale.

2022Cyberwisdom's strategic investment and joint capability established
OntologyThe core engineering discipline
OriginLeads the group's enterprise semantic intelligence work
GroupA Cyberwisdom Group company
What is Origin Big Data?

<b>Origin Big Data is a Cyberwisdom Group company</b> in which Cyberwisdom holds a strategic investment since 2022. Driven by ontology engineering, Origin Big Data bridges the business-data semantic gap to build enterprise semantic intelligence infrastructure. Since 2022 it has worked alongside Cyberwisdom's ontology engineering and development team to provide AI and data application consulting and technical solutions — together establishing the group's Deep Enterprise AI application design capability. Its CEO, Jonas Lim, also serves as SVP of Enterprise AI Consulting within Cyberwisdom Group. Origin Big Data leads the ontology engineering and semantic intelligence work that underpins the group's enterprise data practice.

The relationship

How Origin Big Data sits within the group.

Origin Big Data is a Cyberwisdom Group company. Cyberwisdom holds a strategic investment in the business, and the two have worked together since 2022 on Deep Enterprise AI application design.

Position
RelationshipA Cyberwisdom Group company — Cyberwisdom holds a strategic investment since 2022
Joint capabilityDeep Enterprise AI application design, established together with Cyberwisdom's ontology engineering and development team in 2022
LeadershipJonas Lim — Chief Executive Officer, Origin Big Data; SVP Enterprise AI Consulting, Cyberwisdom Group
Group roleLeads the group's ontology engineering and enterprise semantic intelligence practice
DisciplineDriven by ontology engineering — bridging the business-data semantic gap to build enterprise semantic intelligence infrastructure
The capability

What semantic intelligence infrastructure actually is.

It is the layer that lets an enterprise reason over its own reality — accurately, explainably and with authority.

Ontology engineering

Making business meaning explicit: the entities, the rules that apply to them, the relationships between them, and who owns each concept.

Semantic intelligence

The infrastructure that resolves questions against that model — so an answer traces to a fact, a rule and a version rather than to a similarity score.

AI & data application consulting

Delivered jointly with the Cyberwisdom group: translating data and semantic capability into applications that produce business outcomes.

Ontology as engineering discipline

Using the group's HAKDB model and R-LED-R framework so semantics are testable, versioned and connected to the systems of record.

Where it applies

The enterprise problems semantic intelligence solves.

01

Unreliable AI answers

When output is inconsistent or confidently wrong, the cause is usually missing or implicit business meaning, not model quality.

02

Every team modelling differently

Different groups encode the same concepts differently, so no shared answer is possible — and reconciliation becomes a permanent cost.

03

Rules that live only in people

Critical business conditions are unwritten, so they are inconsistently applied and cannot be tested, audited or automated.

04

AI programmes that cannot scale

Without shared semantics, every new use case rediscovers the business meaning from scratch — and the marginal cost never falls.

Working together

How the engagement runs across the group.

One team, two vantage points

Origin Big Data leads the data and semantics side; Cyberwisdom leads strategy, organisation and delivery. Clients get one accountable team, not a referral.

  • <b>Diagnosis.</b> Cyberwisdom establishes where AI value sits and what the organisation is ready for; Origin assesses the semantic and data estate that would make it possible.
  • <b>Design.</b> The operating model and the ontology are designed together — because an agent's design is only as good as the model it reasons over.
  • <b>Engineering.</b> Origin builds the semantic and data foundations; Cyberwisdom builds the agents, workflows and integration around them.
  • <b>Embedding.</b> Governance, capability and measurement are owned by the group's enterprise practice, with the semantic layer maintained as a governed asset.
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