AI You Can Trust
Responsible & Explainable AI
Trust is essential for AI adoption. We design AI solutions that are transparent, explainable, and governed, so leaders can make confident, ethical decisions. Our AI governance frameworks ensure compliance, mitigate bias, and maintain accountability across all AI initiatives.
Responsible AI, grounded in Microsoft security and compliance
Data & AI on Azure 
Security 
Microsoft Cloud Partner 
Cyber Essentials Plus Key Capabilities
Responsible AI Governance & Ethical AI Consulting
Develop comprehensive responsible AI governance frameworks and ethical guidelines that ensure your AI systems are fair, accountable, and aligned with organisational values.
AI Policy Framework and AI Oversight Strategy
Establish clear AI policies and oversight structures that define decision-making processes, accountability models, and standards for AI development and deployment.
AI Model Transparency & Explainable AI Consulting
Implement explainable AI techniques that make model decisions interpretable to stakeholders, regulators, and end-users, building trust and supporting regulatory compliance.
AI Compliance Management & Regulatory Alignment
Ensure your AI systems meet regulatory requirements including GDPR, AI Act, and industry-specific regulations with comprehensive compliance mappings and documentation.
Data Ethics and AI Accountability Frameworks
Build robust data ethics practices and accountability frameworks that protect your organisation and customers while maximising the value of your AI investments.
Bias Mitigation Strategies & Trustworthy AI Systems
Identify and mitigate bias across training, validation, and production phases with fairness audits, demographic parity testing, and continuous bias monitoring.
AI systems mapped to EU AI Act risk tiers
From assessment to working governance framework
Regulator findings on audited Synapx-built solutions
Faster use-case sign-off with a clear review path
Where Responsible & Explainable AI drives value
Establishing AI governance
Stand up an AI risk register, review board, policies and approval gates so every AI initiative has a clear owner and route to go-live.
EU AI Act readiness
Classify AI systems, document technical files, and build the monitoring and human-oversight controls required for high-risk categories.
Bias, fairness and explainability audits
Independently review existing models for bias, drift and explainability gaps, and implement practical mitigations that satisfy both auditors and users.
Responsible Copilot rollout
Put guardrails around Microsoft 365 Copilot and custom agents — data access, prompt logging, DLP, retention — so adoption is fast but safe.
Regulated industry AI programmes
Help financial services, healthcare and public sector clients satisfy FCA, PRA, ICO, NHS and internal model risk teams with credible evidence.
AI policy and training
Roll out practical AI policies, acceptable use standards and role-based training so the organisation knows what good looks like.
A proven delivery approach
- 01 Step
Assess
Inventory AI systems in use, map risk tiers and review current governance, data and security controls against regulatory expectations.
- 02 Step
Design
Define policies, review forums, roles and tooling for responsible AI, aligned to EU AI Act, NIST AI RMF and Microsoft Responsible AI standards.
- 03 Step
Implement
Deploy controls in Azure AI Foundry, Purview, Entra and Defender; wire up model cards, audit logs and human-in-the-loop workflows.
- 04 Step
Run
Operate the framework alongside your risk and compliance teams, iterating as regulation and your AI footprint evolve.
Frequently asked questions
What frameworks do you align AI governance to?
We align to the EU AI Act, NIST AI Risk Management Framework, ISO/IEC 42001 and Microsoft Responsible AI Standard. For regulated sectors we also layer in FCA, PRA, ICO, NHS DSPT and sector-specific model risk expectations.
How long does it take to stand up AI governance?
A working framework — policies, risk register, review board, model documentation templates and monitoring — typically takes 6–10 weeks to establish. Embedding it across a large enterprise is a 6–12 month programme we can lead or support.
Do you only govern AI you have built?
No. We regularly review and remediate AI systems built by other partners, SaaS vendors or in-house teams. An independent assessment is often the fastest way to understand real AI risk in your organisation.
How do you handle bias and explainability in practice?
We use SHAP, LIME, fairness metrics and Microsoft Responsible AI dashboards during model build and in production. Every model we ship has a model card, documented test results and a human-in-the-loop pattern where appropriate.
Can you help with Microsoft 365 Copilot governance?
Yes. We routinely deliver Copilot readiness programmes covering SharePoint / OneDrive permissions hygiene, Purview sensitivity labels, DLP, retention, prompt and response logging, and user training — so Copilot rollouts are both fast and audit-friendly.
Who typically owns AI governance?
It varies. We usually help clients set up a cross-functional AI council led by the CDO, CTO, CISO or Chief Risk Officer, with legal, HR and business representation. We stay involved as advisors as the framework matures.
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