AIKm institute · Hong Kong Science Park
Machine intelligence for enterprise knowledge
Founded in 2024 and based at Hong Kong Science Park, AIKm is one of Hong Kong's pioneering institutes dedicated to enterprise knowledge management. We research and deploy deep learning and machine learning that turn an organisation's documents, data and expertise into working knowledge and AI Native workflow, while keeping sight of the wider societal impact of these technologies.
Featured courses
Learn AI where it's built
Our most popular programmes, taught in English, Cantonese and Mandarin.
Basic AI & Vibe Coding
A published mini-app and a personal prompt toolkit.
Intermediate Vibe Coding
A deployed app and a repeatable AI development workflow.
Advanced Vibe & Specification-Driven AI Coding
A production-grade project and a spec-driven playbook.
AIKm at a glance
Quick facts about the institute
- Full name
- AI and Machine Learning Institute for Enterprise Knowledge Management (AIKm · AI 知識管理學會)
- Established
- 2024 at Hong Kong Science Park
- Type
- Pioneering AI institute (Hong Kong)
- Location
- 6/F Harbour View 2, 16 Science Park East Avenue, Hong Kong Science Park, N.T.
- Chairman & Chief Scientist
- Ir Dr Hoson H.S. Lam
- Fellow Members
- Prof Kenneth Lam and Dr W.M. Tsang, both Stanford listed top 2% most-cited scientists
- Board Advisors
- Ir Prof John Mok, Prof Wilton Chau, Dr Kelvin Wan (PMI Master Trainer)
- Services
- Applied deep learning research, enterprise AI consulting, professional AI training
- Languages
- English, Cantonese (廣東話), Mandarin (普通話)
- Contact
- director@aikm.ai · +852 2839 8100
What we do
Research, consulting and training under one roof
Three practices that reinforce each other, steered by a farsighted team committed to the responsible application of deep learning: what we learn in the lab shapes our client work, and what we see in the field shapes our curriculum.
Applied ML research
We develop algorithms and reference architectures for enterprise knowledge management: retrieval pipelines, graph construction and evaluation methods, validated against real organisational data.
See research focus →AI strategy & deployment
We help enterprises assess their knowledge management needs, select the right architecture, and implement AI solutions aligned with their strategy, from proof of concept to production.
Discuss a project →Executive & team programmes
Hands-on workshops and structured courses on agentic AI, RAG and generative workflows, designed for enterprise professionals and delivered in English, Cantonese or Mandarin.
View AI courses →Research focus
Where our work concentrates
Five connected areas, from retrieval to governance. Each is described in depth on the research page.
Retrieval-augmented generation (RAG)
Grounding large language models in an organisation's own documents so answers are accurate, current and citable.
Enterprise knowledge graphs
Extracting entities and relationships from unstructured corporate content to make institutional knowledge navigable.
Agentic AI systems
Multi-step AI agents that plan, use tools and act on enterprise systems, with human-in-the-loop controls.
Multimodal & generative AI
Generative models across text, image and video for enterprise use, with attention to provenance and cost.
Responsible AI & governance
Deploying AI in regulated, bilingual business environments: privacy, model risk, auditability and compliance.
Training
Programmes for enterprise professionals
Practical, current and taught by people who build these systems. Cohorts run in-person at Hong Kong Science Park and online.
AI for knowledge work
A grounding in LLMs, prompting and AI-assisted workflows for managers and knowledge workers: what these systems can do, where they fail, and how to adopt them responsibly.
Building RAG & agents
A hands-on course for technical teams: retrieval pipelines, knowledge-graph integration and agentic patterns, built against your own document sets during the programme.
AI strategy briefing
A focused session for leadership teams on AI investment, governance and organisational readiness, grounded in case studies from Hong Kong and regional enterprises.
Community · Past events
Convening Hong Kong's enterprise AI community
In April 2026 AIKm hosted AI & Machine Learning for Enterprise Knowledge Management: From Compliance to Trust at HKSTP Inno2, bringing together speakers from NVIDIA, HKUST/HKGAI, HKU and HKBU on RAG, agentic AI, AI governance and safety. See past events →
Frequently asked questions
Quick answers about AIKm
What is AIKm?
AIKm (AI 知識管理學會) is the AI and Machine Learning Institute for Enterprise Knowledge Management, one of Hong Kong's pioneering institutes dedicated to enterprise knowledge management. Founded in 2024 and based at Hong Kong Science Park, it advances the application of deep learning and machine learning in enterprise knowledge management through applied research, consulting and professional training, guided by a farsighted team focused on the societal impact of AI.
Where is AIKm located?
AIKm is located at 6/F, Harbour View 2, 16 Science Park East Avenue, Hong Kong Science Park, New Territories, Hong Kong. You can reach the institute at +852 2839 8100 or director@aikm.ai.
What does AIKm research?
AIKm's research programme covers five connected areas: retrieval-augmented generation (RAG), enterprise knowledge graphs, agentic AI systems, multimodal and generative AI, and responsible AI governance, all validated against real enterprise data.
What services does AIKm offer enterprises?
AIKm offers three services: applied machine learning research and development, AI strategy and deployment consulting, and training programmes for enterprise professionals. Services are delivered in English, Cantonese and Mandarin, in person at Hong Kong Science Park or online.
How can my organisation work with AIKm?
Contact the institute through the enquiry form on the contact page, by email at director@aikm.ai, or by phone at +852 2839 8100. AIKm collaborates with enterprises, universities, industry bodies and technology partners, and also accepts individual and organisational members.