Design & AI

Why does design & AI matter?

AI can be integrated in different ways: in the background, as suggestions, on demand, in a conversational flow, or through a guided journey. The right format depends on your users, your business context, and how much autonomy you want to give the system. We design AI interfaces that keep that autonomy under control: onboarding, user controls, uncertainty handling, and the right explanations at the right time - including when the AI doesn’t know or gets it wrong.

Make AI actionable in the workflow

Without design, AI stays as a separate “corner” of the product: you get an answer, then you figure out the rest. By designing the right controls and actions - apply, edit, compare, validate - AI becomes a natural step in the journey.

Handle uncertainty without breaking the experience

AI can be confident, uncertain, or wrong. Good design anticipates these states and guides the user: ask for clarification, suggest alternatives, explain a limitation, or switch to a manual option. The result: fewer blockers and fewer workarounds.

Build trust through visible evidence

Trust isn’t declared - it’s built interaction by interaction. By integrating tangible elements, you enable users to verify and stay in control - especially in high-stakes contexts.

When should you focus on design & AI?

You’ve validated an AI use case and now need to turn it into deliverable flows and screens.

Users understand the output, but don’t know how to use it: “OK… now what?”

You need onboarding that teaches people how to use AI well: scope, examples, limits, progressive autonomy.

Errors and uncertain answers create support tickets and drop-offs.

You’re launching predictions and the interface doesn’t tell users what to check or what action to take.

AI patterns vary across teams and the experience becomes inconsistent - messages, controls, levels of explanation.

Ce que nous faisons concrètement

AI onboarding & progressive autonomy

An onboarding flow that puts users in real situations from day one: useful examples, clear scope, common pitfalls, and a gradual learning curve. Goal: reduce false expectations and improve usage quality from the very first days.

User controls

The actions that turn an AI output into something usable: variants, side-by-side comparison, guided editing, explicit validation, undo, and human escalation. That’s what moves AI from “generated text” to “work done”.

Trust design & action-oriented explainability

The right level of explanation, in the right place, depending on context. Sources, drivers, limits, time frame: explainability is built in where it helps people decide and act—not buried in an appendix.

Prototyping AI screens and components

AI-ready screens and components that make the experience usable: input areas, suggestions, controls, history, human escalation, and error states. The result: prototypes ready to test and specify.

Reusable AI guidelines and components

When multiple teams work on AI, we formalise shared rules and components: explanation levels, tone of voice, error states, standard controls. You gain consistency and delivery speed, without reinventing the experience at every AI iteration.

How we work with you

Here are the main steps of the engagement. They adapt to your context, constraints, and decisions to be made. We can start from AI Research deliverables - or directly if framing is already in place.

Together, we clarify the target journey: goals, tasks, high-value AI moments, and product and technical constraints. The idea is simple: define what needs to be designed - and what doesn’t.

Next, we design the AI patterns: onboarding, user controls, uncertainty handling, explainability, edge cases, and error states. The goal is to create an experience that’s robust, consistent, and testable.

From there, we prototype and test: interactive prototypes challenged with realistic scenarios, including failure cases. This validates understanding, control, and next-step action before you build.

Finally, we stabilise for delivery: components, microcopy, consistency rules, and implementation guidance. You speed up release and lay the foundations for continuous improvement.