Implement practical AI safety guardrails and governance - policies, evaluations, content safety, and operational controls - so AI adoption remains controlled and defensible.
AI adoption introduces a new class of operational and reputational risks: unsafe or harmful content, data exposure, unmanaged model behaviour, and uncontrolled change. Microsoft provides Responsible AI guidance and platform capabilities intended to support building and operating AI applications and agents at scale, including Microsoft Foundry documentation that emphasises responsible use of AI.
LW IT Solutions delivers AI safety and governance as an implementable capability. We baseline your AI risk profile, define guardrails aligned to your risk appetite, and implement practical controls across data, identity, application design, and change governance. Where applicable, we implement content safety and content filtering controls (including Azure AI Content Safety and Azure OpenAI/Foundry content filtering) and establish an evaluation and approval workflow so changes remain tested, reviewed, and evidence-backed.
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Service Overview
Highlights
- Practical AI governance focused on implementation, not theory
- Approval workflows and human oversight for high-impact actions
- Defined data boundaries and access controls
- Evaluation and monitoring to detect quality and risk drift
- Designed to evolve as AI usage scales
Business Benefits
- Reduced operational and reputational risk when deploying AI systems
- Clear guardrails that define what AI systems can and cannot do
- Improved control over data usage, model behaviour, and change activity
- Defensible decision-making through logging, evaluation, and evidence capture
- Confidence for sponsors and risk owners that AI use is governed and reviewable
Typical use cases
- Preparing to deploy AI assistants or agents into business processes
- Concerns around data exposure or unsafe outputs from AI tools
- Need for approval and oversight before enabling AI actions
- Multiple teams building AI solutions without consistent controls
- Regulatory, legal, or internal audit scrutiny of AI usage
Objectives & deliverables
What Success Looks Like
- Define clear guardrails aligned to organisational risk appetite
- Establish approval and review processes for AI changes and releases
- Reduce the likelihood of unsafe content, data exposure, or misuse
- Provide evidence and auditability for AI behaviour and decisions
- Create a foundation that supports safe expansion of AI use cases
What You Get
- AI governance and safety blueprint (roles, approvals, guardrails, and evidence model)
- Implemented safety controls in the agreed platform scope (as applicable)
- Evaluation and testing guidance: what to test, how to test, and how to monitor quality and risk drift
- Operational runbooks: incident handling, escalation, and change governance
- A prioritised backlog for iterative improvement as AI usage expands
How It Works
- Discovery - confirm use cases, stakeholders, risk appetite, and chosen/target platform.
- Risk baseline - define the risk scenarios that matter and the guardrails and evidence expectations required.
- Design - agree governance model, approvals, testing approach, and required technical controls.
- Implement - configure guardrails (content safety/filtering where applicable) and operational monitoring paths.
- Operationalise - deliver runbooks, enable owners, and establish a review cadence and improvement backlog.
Engagement Options
- Risk Baseline - Short engagement to assess AI risks and define required guardrails
- Governance Build - Design and implementation of AI safety and governance controls
- Platform Alignment - Governance and safety controls aligned to a specific AI platform
- Advisory Support - Ongoing guidance for internal teams operating AI solutions
Common Bundles
Customers who use this service often bundle with these services
Prompt Evaluation & Testing
Prompt evaluation and testing service defining acceptance criteria, golden datasets, regression checks and quality metrics to control AI outputs.
Prompt Governance & Approval
Prompt governance and approval services providing lifecycle management, ownership, versioning, audit trails, and controlled change for production AI prompts.
RAG / Chat with Your Data
Build governed RAG chat with your data solutions using secure retrieval, permissions-aware context, and measurable answer quality controls.
Data Security Assessment (Purview-led)
Purview-led assessment identifies data risk, validates protection controls, and produces a prioritised roadmap across labels, DLP, and investigations.
Frequently Asked Questions
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