AI Product Intelligence
Risk AI
A decision-support platform where risk signals needed to feel legible, trustworthy, and calm.
42% faster signal scanning
3-step triage model
Reusable AI state library
Problem
Users were facing dense risk information without a clear hierarchy for urgency, evidence, or next action.
Research
Mapped stakeholder mental models, compared AI dashboard patterns, and translated vague model output into user-facing confidence states.
User pain points
Unclear signal priority
Low trust in AI recommendations
Too many equally loud data blocks
UX strategy
Built an interface language around calm escalation: low-friction scanning, evidence trails, and visible uncertainty instead of false certainty.
Wireframes
Started with single-purpose decision panels, then evolved into a modular intelligence workspace.
UI evolution
Moved from saturated AI visuals to restrained graphite surfaces, crisp status cues, and subtle cyan emphasis only where action was needed.
Design system
Created tokens for risk severity, confidence, evidence depth, empty states, and handoff moments.
Final solution
A responsive AI product interface that helps teams see what matters, why it matters, and what to do next.
Reflection
AI interfaces become more humane when they admit uncertainty and guide attention with humility.