Transparent AI use
We explain where AI is proposed, what it will do and where it can be wrong. Client-facing uses should not pretend a machine is a person.
Clear responsibility
Modern capability should come with clear boundaries, responsible data handling and human ownership of important decisions.
This page sets out the working principles Think Menai applies to AI, automation, websites and client systems.
What responsible delivery means
Its role, limits and required review should not be disguised.
The platform, purpose, access and retention need to suit the use case.
Automation does not remove accountability from the business or its people.
Our working standards
The right controls depend on the data, the decision and the possible consequence. We scale the approach to the real risk.
We explain where AI is proposed, what it will do and where it can be wrong. Client-facing uses should not pretend a machine is a person.
Important content, decisions and exceptions need named owners and a practical route for checking or intervention.
We consider purpose, data minimisation, access, retention and supplier terms. A DPIA is recommended where the nature of personal-data processing calls for one.
Live client or customer data should use tools and accounts appropriate to the sensitivity and commercial context, not casual experimental setups.
Access control, appropriate encryption, backups, logging and practical recovery are considered in proportion to the system and risk.
Policies, approved uses, training and a clear tool register help turn good intentions into repeatable behaviour.
Organisational accountability
Think Menai Ltd is registered with the Information Commissioner's Office. Data protection and AI governance questions can be raised directly with us.
Email dataprotection@thinkmenai.com with questions about personal data or a proposed use.
Ask which suppliers, data flows, controls and review steps apply to the work being proposed.
Governance should evolve as tools, regulation, risks and the way a system is used change.
Confidence starts with clear questions
We will explain the practical implications and help shape an approach appropriate to the work.
Discuss your project