We design AI-first interfaces, dashboards, and agentic workflows that people trust.
hyperAIhyperAI
Building AI products requires rethinking traditional software UX paradigms.
Users don't know what the AI did or why
Users drop off before seeing AI value
Users can't correct or guide the AI
We design AI-powered dashboards that surface the right insights at the right time, clean data hierarchy, smart defaults, and contextual AI output display.
AI features on mobile need careful thought. We design AI-native mobile experiences that feel natural, from NLP input flows to adaptive UI states.
AI output feels cold without the right motion. We design micro-interactions that make AI responses feel alive, trustworthy, and intentional.
Interfaces that respond to user behavior, AI state, and context. We design systems that adapt, not just look good on a static mockup.
Whether it's a sidebar assistant, inline suggestion system, or a full chat interface, we design AI copilot experiences that feel like a smart colleague.
From idea to launch-ready AI experiences
Week 1
We start by understanding the problem, business goals, users, constraints, and competitive landscape. For AI products, we also map how the AI behaves, what it outputs, where it fails, and how that shapes the interface.
What we do:
Understand client goals and business context.Define AI feature scope and capabilities.Identify user needs and pain points.Map technical constraints and AI behaviour.What you get:
Discovery report.AI behaviour map.Project scope document.Sprint priorities.Week 2
We turn discovery insights into a clear product direction — information architecture, AI interaction patterns, and a system that can scale with your roadmap.
What we do:
Define product structure and user journeys.Shape AI interaction models and fallbacks.Align UX strategy with technical constraints.Prioritize features for the first release.What you get:
UX strategy brief.Information architecture.AI interaction framework.Release roadmap.Week 3–4
We design high-fidelity interfaces and a reusable system so your AI product feels clear, consistent, and ready for engineering.
What we do:
Craft high-fidelity screens and flows.Build an AI-ready component system.Design empty, loading, and error states.Refine visual hierarchy for trust and clarity.What you get:
UI design files.Design system foundation.Component library.State coverage map.Week 5
We validate the experience with clickable prototypes and feedback loops so decisions are backed by real user signals before build.
What we do:
Build interactive prototypes.Run usability and stakeholder reviews.Test AI-assisted flows with users.Iterate based on validated learnings.What you get:
Clickable prototype.Validation findings.Iteration backlog.Go / no-go recommendations.Week 6
We package everything for a clean engineering handoff and stay close through launch so implementation stays true to the product vision.
What we do:
Prepare specs and developer-ready assets.Walk through edge cases and AI states.Support implementation questions.Review builds against design intent.What you get:
Handoff documentation.Annotated specs.Launch checklist.Post-handoff support.Week 1
We start by understanding the problem, business goals, users, constraints, and competitive landscape. For AI products, we also map how the AI behaves, what it outputs, where it fails, and how that shapes the interface.
What we do:
Understand client goals and business context.Define AI feature scope and capabilities.Identify user needs and pain points.Map technical constraints and AI behaviour.What you get:
Discovery report.AI behaviour map.Project scope document.Sprint priorities.Timelines depend on scope, but every project follows a clear, structured pace from start to finish.
hyperAIOur onboarding drop-off reduced by 37% within the first month.
Wendi Gechter
Head of Growth
−0%
Reduced onboarding drop-off within the first month.Reduced onboarding drop-off
Our demo conversion jumped 2.4× after the new landing page went live.
Wendi Gechter
Head of Growth
$0M
Raised after product redesign.Raised after product redesign.
Our onboarding drop-off reduced by 37% within the first month.
Wendi Gechter
Head of Growth
Our demo conversion jumped 2.4× after the new landing page went live.
Wendi Gechter
Head of Growth
$0M
Raised after product redesign.Raised after product redesign.
Conversion jumped 2.4× after the new landing page went live.
$0M
Raised after product redesign.
AI products have different rules. Here's how design approaches compare.
AI product knowledge
Process & speed
Design thinking
AI product knowledge
Process & speed
Design thinking
AI-native product design is the practice of designing digital interfaces specifically built around AI behavior, including dynamic outputs, probabilistic states, user feedback loops, and adaptive UI. It's fundamentally different from traditional UI/UX design because every screen must account for AI unpredictability and explainability.
AI-native product design is the practice of designing digital interfaces specifically built around AI behavior, including dynamic outputs, probabilistic states, user feedback loops, and adaptive UI. It's fundamentally different from traditional UI/UX design because every screen must account for AI unpredictability and explainability.
Tanjim Islam
CEO of Gr8r
