The Method
Trust is not a feature you add at the end. It is built, or broken, through every design decision along the way.
Trust is not a feature you add at the end. It is built or broken through every design decision along the way.
Diagnose
Where is the challenge?
We begin by mapping your situation, whether that is an existing AI system, a live pilot, an innovation project, or an organisation working out how to engage with AI at all. We identify where the human, organisational, and design gaps are before they become adoption failures.
In this phase we work with: technical leads, product owners, and UX teams to understand what is being built, and with strategy, compliance, legal, and governance teams to understand what it must demonstrate and achieve.
Design
Build the human layer.
We translate requirements (regulatory, organisational, and human) into concrete decisions about interface, interaction, communication, process, and governance. This applies whether you are designing a new AI system, adapting an existing one, or building the internal capability your organisation needs to use AI well.
In this phase we work with: product and UX teams on interaction design, compliance teams on documentation and conformity requirements, and leadership on organisational readiness, change communication, and team enablement.
Validate
Test it against what matters.
We assess the outcome (a system, a process, a governance framework, or a team's capability) against EU AI Act obligations, BITV/WCAG accessibility standards, and real user and organisational needs. We close the loop between compliance, usability, and trust.
In this phase we work with: QA and accessibility specialists on technical testing, users and frontline employees on lived experience, and senior leadership on presenting findings and next steps.
What the Trust Layer assesses
Every assessment maps your AI system against these four dimensions. The output is specific, prioritised, and actionable.
How this differs from standard compliance work
Most EU AI Act support stops at documentation: risk classifications, conformity assessments, policy frameworks. That work is necessary. It is not sufficient.
Trust by Design starts where compliance documentation ends: in the actual interface, the actual interaction, and the actual experience of the person using the system. We translate obligations into decisions.
Questions the Trust Layer answers
sample.body
Can a user understand why your AI made a specific decision about them?
The Trust Layer requires explainability to be designed into the interface, not buried in documentation.
Can they challenge or override it when it is wrong?
Human control is a legal obligation under the EU AI Act for high-risk systems. We design for it.
Can a person with a visual impairment or low digital literacy use the system?
Accessibility is not optional in regulated contexts. We design to BITV/WCAG standards as a baseline.
Does the system communicate uncertainty, or present everything as certain?
Honest communication of confidence levels is a transparency requirement. We build it into the interaction design.
If the AI fails, can the user recover without losing data, time, or dignity?
Recoverability is the most overlooked dimension of trustworthy AI. We design recovery paths before launch.
These are not abstract principles. They are testable, designable, and auditable.
See it in practice
Explore how the Trust Layer has been applied across government, health, and finance, from AI credit decision systems to citizen-facing identity services.
View case studies at trustbridge.design (opens in new tab)Run your own assessment
Use TrustAudit to identify explainability, recovery, accessibility, and control gaps in your AI system before they become compliance or adoption failures.
Go to trustaudit.tools (opens in new tab)Wherever you are with AI, let's talk.
Discovery calls are 30 minutes. Whether you have a live system, a pilot in progress, or a question on a leadership agenda, we'll look at where you are and tell you honestly what would help.
Or email directly: info@jennifersimonds.com