Map the real workflow
We clarify users, data, decisions, handoffs, risk, and the moments where AI should stay out of the way.
Design the system
The solution is shaped as flows, components, prompts, guardrails, evaluation checks, and delivery milestones.
Ship with ownership
You get a usable handoff: docs, next actions, review points, and enough structure for the team to keep moving.
What this is
AI products fail when users cannot understand what the system did, why it did it, or when they should trust it. This service designs the product layer around the model.
The work focuses on trust, transparency, usability, and adoption. That means citations, confidence states, fallback paths, review flows, and interfaces that make the system feel understandable.
How the design work happens
We start by mapping the AI interaction model: what the user asks for, what the system can know, where uncertainty appears, and what the user needs to do next. Then I design flows, states, copy, and interface patterns that make the system easier to judge and control.
The output can be a focused feature redesign, a high-fidelity prototype, a design system extension, or a full AI product interface ready for implementation.
What you get
- User flows for AI-assisted work
- Trust and transparency UI patterns
- High-fidelity Figma prototype
- Design system pieces for implementation
- Developer handoff and QA notes
Best fit
This is best for teams that already have technical AI capability but are struggling with adoption, user confidence, confusing workflows, or unclear product structure.
Design principles
- Show sources and uncertainty where they matter
- Make review, correction, and escalation obvious
- Keep the interface fast enough for repeated daily use
- Design empty, loading, error, and edge states as first-class product moments
Outcome
Your AI feature becomes easier to understand, easier to trust, and easier to adopt.