1 · Private AI Infrastructure
On-premise, managed or hybrid model serving with central operations, capacity planning, monitoring, backup and model portability.
Infrastructure →Institutional AI solutions
Start with the school problem, then choose the infrastructure.
ZYK’s proposition combines deployment, educational applications, institutional knowledge, assessment, governance, training and support. Schools can begin with a bounded pilot and expand toward a shared institutional AI environment.
Five solution pillars
2 · Education AI Platform
Chat, creation, analysis, voice, coding and agents, supported by institutional Knowledge, Assess and Control layers.
Platform →3 · Governance & Compliance
Identity, permissions, consent, retention, filtering, audit, approval workflows, documentation and readiness assessment.
Governance →4 · Training & Capability
Role-based programmes for teachers, leaders, IT teams, students and parents, plus ongoing capability development.
Training →5 · Partnerships & Academy
Host School, Graduate Academy, university and future Innovation Lab pathways for capability and ecosystem development.
Academy →High-value education use cases
Infrastructure becomes valuable when it solves repeatable institutional problems.
Curriculum-aware AI
Ground approved assistants in curriculum, rubrics, handbooks, policies and internal resources through governed retrieval.
ZYK Knowledge →Assessment & exams
Mock exams, question banks, listening/speaking workflows, adaptive assessment concepts, feedback and analytics.
ZYK Assess →Teacher productivity
Planning, differentiation, resource creation, rubric-aware feedback and administrative drafting with human review.
Student learning
Private tutoring, language practice, coding, creation and AI literacy inside role-appropriate institutional controls.
School operations
Bounded assistants for admissions, library, IT helpdesk, HR, finance, policy retrieval and defined support workflows.
Model governance
Separate the school experience from the underlying model so approved models can evolve without rebuilding every workflow.
AI Gateway →Scale beyond one campus
One architecture, different levels of control.
Individual school
A private environment with local identity, knowledge, policy and educational workflows.
School group
Shared standards, selected infrastructure and central governance with campus-specific knowledge and permissions.
Education bureau / region
A future regional service layer for shared capacity, model evaluation, governance baselines, training and assessment services.
Regional architecture →Adoption path
Assess
Map infrastructure, data flows, stakeholders, current AI use, priority workflows and governance gaps.
Pilot
Choose a bounded group of teachers, classes or operational users and define measurable use cases.
Integrate
Connect identity, LMS, approved knowledge, policies and support processes according to scope.
Scale
Expand capacity, users, training and governance only after evidence from the pilot supports the next step.
This page combines core business-plan concepts with clearly identified product directions under development. Final capability, integrations and commercial scope depend on validation and contract.