Frame the goal
Give users the context, constraints, examples, and guidance needed to ask well.
01 / Human–AI decision loop
Design every handoff between human intent and machine output.
Useful AI is a loop, not a single response. The experience must help people express intent, judge results, intervene, and recover with confidence.
Reveal the system
Show progress, sources, assumptions, and system status while work is happening.
Support judgment
Help users assess relevance, quality, confidence, and what requires attention.
Keep agency
Make approval, editing, correction, undo, and escalation available at the right risk level.
Handle uncertainty
Create useful paths for poor inputs, missing data, model limits, and failed outcomes.
02 / Service focus
AI product and interaction design
Design the contract between people and AI.
We turn model capability into a usable product by defining what people ask, what the system reveals, and where users can review, correct, or take control.
The challengeAI creates value only when people understand what happened, why it matters, and what they can do next.
Intent and prompting
Help users express goals with the right context, constraints, examples, and guidance—without making them learn prompt engineering.
Trust and explainability
Show sources, confidence, system status, and limitations at the moments where they change a user decision.
Control and recovery
Design approval, correction, undo, escalation, and fallback paths so automation never becomes a dead end.
When you need this
- Users do not know what to ask or how to judge an AI response.
- Automation needs review, approval, or correction before it can be trusted.
- Confidence, source, error, and loading states are still undefined.
What changes
- 01AI interactions users can understand
- 02The right balance of automation and control
- 03Clear states for confidence, errors, and uncertainty
- 04Patterns that scale across AI features
03 / Ways to engage
Start at the level your product needs.
Each option creates a useful outcome on its own. The right scope depends on how much clarity already exists and how far the work needs to travel.
01Diagnostic
AI UX risk review
A review of trust, control, explainability, failure states, and how the AI capability fits the user workflow.
02Prototype sprint
Human–AI interaction prototype
A testable experience for one AI workflow, covering prompts, outputs, review, correction, and recovery.
03Partnership
AI product design
End-to-end product strategy and UX/UI for copilots, intelligent automation, recommendations, or generative tools.
04 / Process & deliverables
From direction
to release.
Frequently asked questions
Questions before
we start.
Clear answers about scope, collaboration, and what your team can expect.
Do you need access to our model?
Not initially. We can define the experience around capabilities, limitations, user goals, and representative outputs.
Can you design generative AI and analytics products?
Yes. We design copilots, workflow automation, recommendations, forecasting, and AI-assisted analytics.
How do you approach trust?
We make system status, sources, confidence, reversibility, and user control explicit in the experience.
Tell us what you are building. We’ll reply with the clearest next step—usually within a few hours.
Senior-led from day oneReply within a few hours