AI features people actually trust.

Interfaces for AI products — designing for uncertainty, confidence and graceful failure.

Why it matters

AI products break classic UX rules: outputs vary, confidence matters, and failure needs grace. We design AI experiences that set honest expectations, show their reasoning, and keep the human comfortably in control.

What we deliver

01

Chat & Agent Interfaces

Conversational UIs with clear affordances — what it can do, what it can't.

02

Confidence & Explanation

Showing sources and certainty so users know when to trust and when to check.

03

Human-in-the-Loop Flows

Review, approve and correct patterns that keep people in charge.

04

Graceful Failure

When AI is unsure, the design catches it — fallbacks that keep trust intact.

Our Process

How we work

01

Research

Users, goals and constraints first — we design for the person, not the pixel.

02

Wireframe

Structure before style: flows and layouts agreed while changes are cheap.

03

Design

High-fidelity screens, components and interactions crafted in Figma.

04

Handoff & Iterate

Developer-ready specs, then refinement from real usage data.

Toolbox

FigmaDesign systemsPrototypingUser flowsAccessibility

FAQ

Common questions

Why does AI need special UX?

Because output varies. Users need to calibrate trust — and that calibration is a design problem, not a model problem.

Can you retrofit AI into our existing product?

Yes — the best AI features often live inside familiar flows, not in a bolted-on chat window.

How do you prevent users over-trusting the AI?

Source citations, confidence signals and friction on high-stakes actions — trust is designed, not assumed.