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Govern AI before it becomes everyone's experiment

Create the guardrails your organisation needs to use AI safely. We help define AI governance, data protection, Microsoft Copilot controls, Purview readiness, usage policies, security requirements and operating models for responsible enterprise AI adoption.

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Make AI useful, secure and manageable

Responsible AI Governance

AI adoption creates new questions for data security, privacy, access, licensing, usage, risk and accountability. Without clear governance, tools spread quickly, sensitive data can be exposed and teams may not know which AI services are approved for business use.

Synenza helps organisations establish practical AI governance across Microsoft Copilot, Copilot Studio, AI agents, Azure OpenAI, Microsoft Purview and broader enterprise AI platforms. The focus is to enable innovation while protecting company data, reducing risk and giving teams clear rules for safe adoption.

What we deliver

Built for the work — not for the deck.

Policy

AI usage policy and operating model

Define how AI tools, copilots and agents should be requested, approved, used, monitored and supported across the organisation.

Purview

Microsoft Purview readiness

Review Microsoft Purview capabilities such as sensitivity labels, data loss prevention, audit, retention, information protection and compliance controls for AI adoption.

Data

Data protection and access controls

Assess permissions, data exposure, oversharing risks, labels, sensitive information types and access patterns before AI tools interact with company information.

Copilot

Microsoft Copilot governance

Prepare governance for Microsoft 365 Copilot, Copilot Studio agents and Dynamics 365 AI experiences, including data access, user readiness, security and adoption controls.

Risk

AI risk and compliance review

Identify governance requirements for privacy, security, model use, human oversight, auditability, external AI services and responsible AI decision-making.

Controls

Licensing, tokens and platform controls

Review AI licensing, usage controls, model access, token consumption, environments, connectors, approvals and platform boundaries for managed AI adoption.

How we work

A measured, honest path from idea to production.

Understand

Review your current AI usage, Microsoft environment, data landscape, security posture, compliance obligations and business expectations.

Assess

Evaluate governance readiness across policy, data protection, access controls, Microsoft Purview, Copilot, agents, licensing and platform usage.

Define

Create practical governance recommendations, operating rules, roles, approvals, security controls and AI usage guidance for business and technology teams.

Enable

Support rollout of governance practices with templates, decision guides, awareness material, technical controls and a roadmap for continuous improvement.

Use Cases

Common business scenarios.

Microsoft Copilot governance

Prepare policies, permissions, Purview controls, adoption guidance and data protection measures before expanding Microsoft 365 Copilot across the organisation.

AI agent and custom copilot governance

Define how internal agents and custom copilots should access data, call tools, use connectors, trigger workflows and operate within approved security boundaries.

Enterprise AI usage and risk management

Create clear rules for approved AI tools, external model usage, sensitive data handling, token consumption, audit requirements and responsible AI practices.

Outcomes you can defend

What good looks like.

A clear AI governance model covering Microsoft Copilot, custom copilots, AI agents and external AI tools.
Practical recommendations for Microsoft Purview, sensitivity labels, data loss prevention, audit and information protection.
Improved visibility of data access, oversharing risks, sensitive information and AI exposure points.
Defined AI usage policies, approval paths, roles, responsibilities and operating controls.
Guidance for managing AI licensing, token usage, platform access, connectors and environments.
A roadmap for responsible AI adoption that supports innovation while protecting company data.

Frequently asked

The questions clients ask first.

What is AI governance?

AI governance is the set of policies, controls, roles, processes and technology decisions that guide how Artificial Intelligence is selected, approved, used, monitored and improved within an organisation.

Why is AI governance important for Microsoft Copilot?

Microsoft Copilot works with organisational data that users already have permission to access. Good governance helps manage permissions, sensitivity labels, data loss prevention, auditing, user adoption and secure usage before Copilot is broadly deployed.

How does Microsoft Purview support AI governance?

Microsoft Purview can support AI governance through information protection, sensitivity labels, data loss prevention, audit, retention, compliance controls and visibility across sensitive data and AI-related interactions.

Can Synenza help govern custom copilots and AI agents?

Yes. Synenza can help define governance for custom copilots and AI agents, including data access, tool permissions, connector usage, workflow actions, human oversight, logging, monitoring and secure deployment patterns.

How do we manage staff use of external AI tools?

Organisations should define approved tools, data handling rules, usage boundaries, risk categories, monitoring expectations and escalation paths for external AI services. Synenza can help create practical guidance and controls that teams can follow.

Does AI governance slow down innovation?

Good governance should make AI adoption safer and easier, not slower. Clear rules, approved patterns and practical guardrails help teams move with confidence while protecting business data and reducing unnecessary risk.

Let's scope a first conversation.

Tell us what you're trying to do. We'll come back with a point of view, not a sales pitch.

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