The gap between a legally compliant AI system and one that is genuinely trusted is a design problem.
The gap no one is designing for
Your organisation is moving towards AI.
You have ambition, budget, and pressure to act. You may have a pilot running, a vendor shortlisted, or a leadership mandate to deliver.
But is your organisation actually ready?
Technology is the easy part. What derails AI adoption is the human layer: trust, communication, governance, accessibility, and organisational readiness. These are design problems, and they need to be solved early, not retrofitted at the end.
We work with organisations at every stage, from early exploration and innovation through to production deployment and compliance. The earlier you address the human layer, the less it costs to get right.
Where AI adoption breaks down
Most EU AI Act compliance work lives in the legal column. Most product work lives in the technical column. We work across both, translating obligations into implementable decisions.
What makes this work
Most AI adoption challenges are not technology problems. They are human, organisational, and design problems, and they show up at every stage, from the first internal conversation about AI through to production deployment and ongoing governance.
The missing piece is someone who can work across all of those stages and translate between all of the people involved.
AI Adoption
Moving organisations from AI ambition to working systems people actually use, at whatever stage you are at.
AI Enablement
Building internal capability so your teams, from frontline employees to leadership, can engage with, govern, and get value from AI confidently.
Human-Centered AI
Designing AI systems and AI adoption processes around the people who use them: their needs, their limits, their trust.
Responsible AI
Translating EU AI Act obligations, ethics frameworks, and governance requirements into real decisions, in innovation, in procurement, and in production.
Digital Transformation
Connecting AI adoption to wider organisational change: processes, culture, communication, and readiness.
Workshop Facilitation & AI Governance
Running working sessions that move teams from uncertainty to action, and presenting findings to C-suite in language that lands.
Whether your AI is a finished system, a live pilot, or still a question on a leadership agenda, this is where we start.
From legal obligation to user trust
Every EU AI Act obligation has a design consequence. We make that consequence specific, testable, and implemented, not just documented.
Three ways we work with you
Trust Audit
We assess your AI system or AI adoption plans against the four Trust Layer principles, explainability, recoverability, accessibility, and human control, and show you exactly where the gaps are, whether you are in discovery or in production.
trustaudit.tools → (opens in new tab)Framework Implementation
We design and build the Trust Layer into your AI systems, innovation projects, and organisational processes, working alongside your technical, product, UX, compliance, and leadership teams from early exploration through to deployment.
EU AI Act Readiness
We map your high-risk AI obligations, current and anticipated, and build the human-centred compliance layer your organisation needs. Enforcement is underway. We help you move from documentation to implementation.
We work with regulated industries deploying high-risk AI
Government
Federal agencies, ministries, and public institutions deploying AI in citizen-facing services.
AI decisions in citizen services must be explainable, contestable, and accessible to all users including those with disabilities or low digital literacy.
Healthcare
Hospitals, insurers, and health technology companies using AI for diagnosis, triage, or patient decisions.
AI recommendations that influence diagnosis, triage, or treatment must be transparent to clinicians and patients, with clear human oversight at every decision point.
Finance
Banks, insurers, and financial institutions using AI for credit, fraud, or eligibility decisions.
AI credit, fraud, and eligibility decisions carry legal explainability obligations under both the EU AI Act and GDPR that must be designed into the system, not added afterwards.
Built on research. Validated in practice.
The Trust by Design framework was developed through independent research across 14+ AI implementation teams in the German public sector, and validated through advisory work with regulated organisations across government, health, and finance.
We don’t consult from the outside. We’ve built government AI systems from the inside, including Germany’s first BITV-certified government application, with over a million users.
i-Kfz · Germany’s first BITV-certified government app · 1M+ downloads · Presented to 6+ German government communities · MA Design for Responsible AI · EU AI Act specialist
The Trust Layer
The Trust Layer is not a checklist. It is a design framework. Four dimensions that must be present for an AI system to be trustworthy, not just compliant.
A connected practice
Trust by Design is one part of a three-layer professional practice. Each layer can be used independently or together.
Trust by Design
The framework, the method, and the professional practice. Start here to work with us directly.
TrustAudit Tools
Run a structured Trust Layer assessment on your own AI system. Identify gaps in explainability, oversight, and accessibility before they become compliance failures.
Run an audit ↗ (opens in new tab)TrustBridge Design
See how the Trust Layer has been applied in practice, across banking, education, health, and data consent. Real systems, real users, real design decisions.
See the work ↗ (opens in new tab)Ready to build trustworthy AI?
Discovery calls are 30 minutes. No obligation.