Services
UX/UI Design
Research-driven design systems that people actually use, accessible and scalable from day one.
The best-engineered system fails if people route around it. Interfaces designed from assumption instead of research consistently produce software that’s technically correct and practically unused.
The accessibility half of that problem is measurably getting worse, not better. Audits across the web's most-visited pages now find WCAG failures on the overwhelming majority of them, reversing several years of prior improvement, at the same time as accessibility litigation citing these same standards has been climbing sharply. Retrofitting compliance after launch is always the more expensive path, and increasingly the riskier one too.
Our design practice starts with research — real users, real workflows — before a wireframe gets drawn, and accessibility is built in from that first stage rather than audited in afterward: personas and journeys reflect a real range of cognitive and motor ability, and wireframes get evaluated against WCAG 2.2 before visual design even begins. Design systems ship with accessible components by default, so accessibility compliance is a property of the system, not a checklist run once before launch. The same practice now covers the emerging patterns specific to AI-driven interfaces — how a confidence score, a citation, or a human handoff actually gets shown to someone using the product.
Handoff structure gets the same design attention as the interface itself, particularly for AI-driven features: what a confidence score looks like without reading as a system error, how a citation sits next to a generated answer without cluttering it, and exactly what information transfers when a decision hands off to a person — the case summary, what's already been tried, and why it escalated — so a human picking it up isn't starting from zero. These are still-forming patterns specific to AI products, not something a standard component library already solves.
Frequently asked
When should accessibility work start in a design process?
At the very beginning — reflected in personas and journey maps, then checked against WCAG 2.2 at the wireframe stage, before visual design begins. Auditing for accessibility after a design is finished is far more expensive than designing it in from the first sketch, and it shows in the result either way.
Do you design the interface, or build it too?
Both, through the same team — design and engineering aren't handed off between separate vendors, which is specifically what avoids the gap where a beautiful design turns out to be impractical to build, or an engineering-led build ships without the research behind it.
What does "AI interface pattern" design actually mean in practice?
How you show a confidence score without it reading as an error, how a citation sits next to an AI-generated answer without cluttering it, and exactly when an interface should hand a decision to a person instead of the model — these are still-settling design problems specific to AI features, not solved by a standard component library.
Is accessibility non-compliance actually a legal risk, or just best practice?
Increasingly both, and the legal side is moving faster than most teams expect — accessibility lawsuits citing these standards have been climbing sharply over the past year, and WCAG 2.2 AA conformance is now the explicit legal benchmark for US federal sites under the DOJ's rule, with state and local government sites on a compliance deadline through 2027–2028. Building it in from the first wireframe is cheaper than defending it later either way.