LLM Governance & Security Controls
Controlling AI Behaviour in Enterprise Environments
Large Language Models (LLMs) provide powerful capabilities for automation, knowledge management, analytics, and decision support. However, without appropriate governance controls, organisations can be exposed to risks including prompt injection, prompt engineering attacks, data leakage, inaccurate responses, and policy violations.
Triatin helps organisations implement governance frameworks and security controls that allow AI solutions to operate safely, consistently, and within defined business boundaries.
Why LLM Governance Matters
Enterprise AI systems must be designed to:
- Protect sensitive information
- Prevent unauthorised actions
- Maintain compliance requirements
- Enforce business rules
- Reduce hallucinations
- Improve response consistency
- Protect intellectual property
- Support audit and governance requirements
Governance Controls
Prompt Wrappers
Prompt wrappers provide a controlled interface between users and AI models, ensuring that all requests are validated, monitored, and constrained before reaching the LLM.
Typical controls include:
- User input validation
- Policy enforcement
- Context filtering
- Response restrictions
- Action approval workflows
- Content moderation
Prompt Injection Protection
Prompt injection attacks attempt to override system instructions or manipulate model behaviour.
Mitigation strategies include:
- Input sanitisation
- Context isolation
- Role separation
- Instruction hierarchy enforcement
- External content filtering
- Tool access restrictions
Data Protection
Prevent exposure of sensitive information through:
- Data classification controls
- Role-based access controls
- Source validation
- Output filtering
- Audit logging
- Secure retrieval mechanisms
Guardrails and Policy Enforcement
Governance frameworks can enforce:
- Regulatory requirements
- Organisational policies
- Industry standards
- Security controls
- Ethical AI principles
- Operational restrictions
Enterprise AI Architecture
A governed AI environment typically includes:
- User Interface
- Authentication and Authorisation
- Governance Layer
- Prompt Wrapper
- Policy Engine
- Retrieval and Knowledge Services
- LLM Services
- Monitoring and Audit Framework
This architecture ensures that users interact with a managed AI service rather than directly accessing the underlying model.
Common Use Cases
Internal Knowledge Assistants
Control access to corporate information while maintaining auditability and security.
Customer Service Agents
Ensure responses comply with organisational policies and approved information sources.
Operational AI Systems
Restrict actions and recommendations to approved workflows and business rules.
AI-Powered Reporting and Analytics
Provide controlled access to data while preventing unauthorised disclosure.
How Triatin Can Help
Triatin designs and implements governance frameworks for AI solutions, including prompt wrappers, policy engines, access controls, audit frameworks, retrieval governance, and secure agent architectures.
Our focus is enabling organisations to realise the benefits of AI while maintaining security, compliance, and operational control.
Secure AI. Trusted outcomes. Governed intelligence.