About Work AI Expertise
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I'm Shailly Gadhiya, a UX Designer building scalable product experiences at the intersection of human behavior and AI.

Designing clarity. Driving measurable product impact.

My approach blends rigorous research, systems thinking, and a keen eye for visual design — I've worked across B2B SaaS, consumer apps, and emerging AI-powered products.

User Research Interaction Design Design Systems Prototyping Usability Testing AI Product Design
Always up for coffee and networking!
5+
years designing digital products
40+
end-to-end UX projects
12+
cross-functional teams · ADAC, Bosch Rexroth, Audi, Volkswagen
Selected Work

Designing for Real-World Impact

View all Work
MAN Parts
  • Genuine Parts & Accessories
  • B2B Digital Platform
  • End-to-end user journey
Redesigning a large-scale automotive parts platform to simplify search, selection, and ordering.
MAN Genuine Parts & Accessories
ADAC Fahrzeugwelt
  • Automotive UX
  • Vehicle marketplace platform
  • User interface redesign
Designing an automotive experience that balances rich content with intuitive navigation.
ADAC Fahrzeugwelt
Antarctica Exploration
  • UX Research & Strategy
  • Emotion-led Experience Design
  • Luxury Travel
Luxury travel UX · Turning exploration into seamless booking journeys.
Wanderlust — Silversea Cruises
Design Metrics Benchmark
  • User Research
  • UX Benchmark Framework
  • Metrics & KPI design
Developing a UX benchmarking framework to quantify design quality and decision-making.
Design Metrics for UX Benchmark — User Research
Bulk Classification
  • AI-Assisted UX
  • Data classification tool
  • Complex workflow design
AI-assisted UX · Reducing manual effort through intelligent classification.
Bulk Classification
Linda Water Assistant
  • Water AI Assistant
  • University Project
  • Politecnico di Milano
Conversational AI UX · Making complex utilities accessible to everyday users.
Linda — Water Assistant (Politecnico di Milano)
AI Expertise

Designing Human-Centered AI Experiences

AI is only valuable when people can understand, trust, and effectively use it. My approach focuses on designing AI-powered systems that reduce complexity, support human decision-making, and scale responsibly across real-world constraints.

01

Define the AI Opportunity

Identify where AI meaningfully reduces user effort or operational complexity — not where it simply adds automation.

Bulk Classification
↑ Prevents feature-driven AI that adds complexity without user value
02

Understand Users & Mental Models

Study how users interpret AI outputs, set expectations around accuracy, and decide when to trust or override the system.

Linda — Water Assistant
↑ Prevents automation surprises, over-reliance, and loss of user trust
03

Design AI-Driven Interactions

Create interaction patterns that balance automation with transparency and user control — letting users review, adjust, and correct rather than accept results blindly.

Bulk Classification
↑ Avoids opaque "black-box" behaviors users can't understand or intervene in
04

Prototype & Test in Real Contexts

Validate AI behavior across edge cases, error states, and confidence variations — not just ideal scenarios.

Design Metrics
↑ Reduces risk of misleading outputs and unsafe user actions
05

Build Trust & Responsibility

Design feedback loops, explanations, and safeguards that help users understand system behavior and limitations — especially when AI cannot provide a definitive answer.

LindaBulk Classification
↑ Prevents blind trust, misuse, and long-term reputational risk
06

Launch, Monitor & Evolve

Treat AI UX as an ongoing system that evolves with data, usage patterns, and user expectations — accounting for long-term scalability and changing workflows.

MAN — Genuine Parts
↑ Ensures reliability and usability as systems grow and evolve
"

Great AI UX isn't about intelligence — it's about clarity, responsibility, and trust at scale.

Contact

Let's build something great together

Whether you're looking for a design partner, want to discuss AI-powered experiences, or just want to grab a virtual coffee — I'd love to hear from you.

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