Singapore · Group HeadquartersHong Kong · Mainland China · 20+ countries served
Our history

Twenty-five years of building capability — and the discipline to keep adapting it.

Cyberwisdom began by solving a specific, unglamorous problem: organisations needed to know who was trained to do what, and be able to prove it. Almost everything the group does today is a scaled-up version of that problem.

How long has Cyberwisdom been operating?

Cyberwisdom's business was founded in <b>1999</b>, beginning with enterprise learning management systems for Hong Kong's banking, insurance and professional sectors. Over the following two decades the group built out training and CPD management, compliance learning, knowledge and competency management, business simulation, custom courseware and managed learning services. In the 2020s it extended the same organisational discipline into <b>enterprise AI, business ontology and enterprise data</b> — establishing its Deep Enterprise AI application design capability with Origin Big Data in 2022, and launching the LyndonAI enterprise AI platform family.

Timeline

From compliance training to enterprise AI.

1999
Founded in Hong Kong

Cyberwisdom begins by building enterprise learning management systems for Hong Kong's banking, insurance and professional-body sectors — organisations that had to prove who was trained to do what.

2000s
wizBank becomes the flagship platform

The wizBank enterprise LMS platform establishes Cyberwisdom's core proposition: one suite covering the full training lifecycle — build, deliver, assess, certify, report — with dedicated cloud, standard SaaS and on-premise deployment options.

2010s
Beyond the LMS: CPD, compliance and knowledge

CPD management, compliance learning, competency management, knowledge management, business and sales simulation (MetaSim), managed learning services and bespoke courseware extend the group's remit from training records into organisational capability.

2020s
Deep Enterprise AI and Origin Big Data

In 2022 Cyberwisdom establishes its Deep Enterprise AI application design capability with Origin Big Data, combining ontology engineering with AI and data application consulting to build enterprise semantic intelligence infrastructure.

2020s
The wizBank 8.0 platform generation

The flagship platform moves to wizBank 8.0 with a Capability Ontology and capability graph, an enterprise behaviour digital twin in MetaSim, and the LyndonAI enterprise AI platform family — UpLearn LMS, Kora knowledge management, MetaSim and LyndonAI as four connected systems.

2020s
Context, governance and agentic operations

ContextOrgin extends the practice into enterprise GraphRAG management, while ComplyAI brings ISO 42001-aligned AI management system compliance into the group's own delivery toolkit.

Today
Cyberwisdom Group

A Singapore-headquartered group of more than 300 consultants and technical specialists, serving over 800 enterprise clients across 20+ countries and regions across three connected practices: enterprise AI and ontology, enterprise data, and enterprise learning.

Why the history matters

We are not new to this. We are new to the label.

It would be easy to read an enterprise AI practice as a pivot. Ours is closer to a widening.

The lineage is real

Ontology-based knowledge management, competence modelling, workflow design, simulation and auditability are exactly the capabilities enterprise AI needs. We built them for learning. Enterprise AI applies them to the whole organisation.

Regulated-industry DNA

Banks, insurers and professional bodies do not tolerate ungoverned change. The group learned in a sector where evidence, accountability and audit trails are non-negotiable — conditions that enterprise AI adoption now requires everywhere.

Implementation, not just advice

The group has always owned delivery. It has run platforms, produced content at scale, operated learning services and supported live regulatory obligations — not merely produced recommendations.

Change has to be adopted

Two decades of learning deployment taught us the hardest lesson in enterprise AI: a solution nobody adopts has no value, regardless of how well it works technically.

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