AI agents for defined work, with defined authority.
MajuWorks Agents can perform specified tasks involving language, context and multi-step reasoning. Each agent is designed around an approved use case, authorised tools, data boundaries, human accountability and an escalation path.
More than a chatbot. Less than unrestricted autonomy.
An AI agent can interpret an objective, use approved information and tools, and take permitted steps within a workflow. Its authority should be limited according to the business consequence of the task. MajuWorks does not position agents as employees or promise error-free autonomous operation.
Bounded, reviewable work
- Classify & route enquiries
- Extract from approved documents
- Prepare draft quotations
- Summarise exceptions for review
Higher-consequence actions
- Final financial commitments
- Irreversible transactions
- External communications carrying liability
- Employee or legal decisions
Start with bounded, reviewable work.
Examples:
- Classify and route incoming enquiries.
- Extract structured information from approved documents.
- Prepare draft quotations from authorised data.
- Summarise operational exceptions for review.
- Draft responses using approved knowledge sources.
- Identify missing information and request completion.
- Monitor defined conditions and prepare recommended actions.
Whether an agent may execute an action, prepare a draft or only recommend a next step depends on the approved risk assessment.
Higher-consequence work requires tighter boundaries.
Examples include final financial commitments, employee decisions, legal conclusions, safety-critical actions, unrestricted database writes, irreversible transactions and external communications carrying material liability. These require explicit ownership, suitable expertise, stronger controls and, where appropriate, human approval.
Governance is implemented in the system.
Controls may include:
- Defined use case, success criteria and prohibited actions
- Least-privilege identity and tool access
- Approved data sources and retrieval boundaries
- Human approval at material checkpoints
- Output validation and policy checks
- Test scenarios covering normal, adversarial and failure conditions
- Logging of prompts or instructions where appropriate, tool calls, actions, approvals and outcomes
- Monitoring, exception review and override analysis
- Version control, staged release, suspension and rollback
- User disclosure, training and escalation contacts
Do not claim that an agent's private chain-of-thought or internal reasoning is captured or audited. Describe observable instructions, tool calls, actions, approvals and outputs instead.
Designed with reference to Singapore's agentic AI guidance.
MajuWorks designs agent implementations with reference to the current Model AI Governance Framework for Agentic AI published by Singapore's Infocomm Media Development Authority. The framework addresses upfront risk bounding, meaningful human accountability, lifecycle controls and responsible end-user use. This statement describes a design reference; it is not a claim that MajuWorks or every deployment is IMDA-approved or certified.