Systems designed to be understood and operated.
MajuWorks documents system boundaries, data ownership, interfaces, permissions, controls and support responsibilities so business and technical owners can evaluate how the solution will operate.
A layered operating environment.
The actual architecture, providers, hosting arrangement and data locations are documented for each deployment.
Questions the design must answer.
- Which system owns each important data object?
- How are users, services and agents authenticated?
- How are permissions granted, reviewed and removed?
- Which interfaces can write to production records?
- Which actions require approval?
- What activity is logged and for how long?
- How are integrations monitored and reconciled?
- How are changes tested, approved and released?
- How are failures detected, escalated and recovered?
- What are the backup and restoration arrangements?
- Where is customer data processed and stored?
- How are third-party providers and models assessed?
- What happens to data, configurations and documentation when service ends?
Controls are selected according to the deployment.
Security and personal-data protection depend on the systems, data and responsibilities within scope. Relevant measures may include access control, multi-factor authentication, encryption, environment separation, secure secret management, vulnerability management, backups, logging, incident procedures, retention controls and supplier assessment.
Organisations remain responsible for meeting applicable obligations under Singapore’s Personal Data Protection Act. MajuWorks documents its role and relevant processing responsibilities for each engagement. Do not use a generic "PDPA compliant" badge as a substitute for describing actual practices.
Governance for agents that can act.
Assess and bound risk
Select appropriate use cases and limit action space, access and autonomy.
Meaningful human accountability
Name responsible owners and place approval checkpoints at material decisions.
Technical controls and processes
Apply lifecycle testing, access controls, guardrails, logging, monitoring and change management.
Responsible end-user use
Explain capabilities, limits, data access, responsibilities and escalation; provide appropriate training.
This approach is designed with reference to IMDA's current Model AI Governance Framework for Agentic AI. It is a design framework, not a claim of certification.
Trust should be supported by documentation.
Possible artefacts: architecture diagram; data-flow map; role and permission matrix; integration specification; risk assessment; agent use-case specification; test plan and results; change log; operating runbook; incident and escalation procedure; data-processing terms where applicable.
What we will not claim without evidence.
- IMDA approval or certification
- AI Verify certification
- Guaranteed accuracy, savings or return on investment
- Full auditability of an AI model's private reasoning
- Singapore-only data hosting unless contractually verified
- 24/7 service or contractual response times unless included
- Compliance with every law or sector requirement without a scoped assessment