The problem
A new category to explain
Most review tools stop at positive or negative. nrtureAI goes much further, and the design had to make that clear fast.
Case study · Hospitality · AI platform
Thousands of reviews, turned into clear decisions.
nrtureAI reads every guest review, shows what moves spend, and replies in the brand's voice. I led design for the website and the dashboard.
- Client
- tRetail Labs
- Industry
- Hospitality · AI review intelligence
- Product
- Marketing website and analytics dashboard
- Timeframe
- 2025 · Ongoing
- My role
- Lead designer: UX research, wireframing, visual design, design system, prototyping
- Tools
- Figma, FigJam
- Links
- Visit nrture.ai
01 · The short version
The project in a minute
What I did
Two surfaces, one system
Structured a website that sells a new idea, and a dashboard that turns complex review data into answers.
The result
From reviews to actions
Operators see one score, ask Elara questions in plain words, and spot where the experience slips.
2surfaces: website and dashboard
8+experience attributes charted over time
5venue types, from hotels to airports
2very different clients on one system
02 · Who it's for
Built for people who run venues
Restaurant, hotel and airport managers don't have time to read every review. They need to know what to fix, and where.
Primary users
Restaurants · Hotels · Airport F&B · Attractions · Multi‑venue operators
“Tell me what guests really think, and what I should do about it today.”The brief in one line, as I framed it
- Explain it fastThe value is clear in the first scroll.
- AI that feels humanElara is warm and on‑brand, not a bot.
- Earn trust earlyStats, logos, testimonials and clear pricing.
- Tame complex data8+ attributes, peers and venues, read at a glance.
- Scale across venuesOne system for an airport food court or a wine region.
03 · How it came together
Research, structure, design
A new category needs the story worked out before the pixels.
- 1
Step 1
Research
Studied how leading SaaS and AI products tell their story, and listed open questions for the team.
- 2
Step 2
Structure
The website flow: hero, the problem, meet Elara, product, then proof and pricing.
- 3
Step 3
Design & review
Visual language, the dashboard, and written design reviews after every round.
04 · Key decisions
The choices that made it work
Decision 01
Introduce the AI as a person
- Why
- Generic AI feels cold. Operators need to trust who's replying to their guests.
- What I did
- Elara is shown as a person with three simple promises: she reads every review, understands emotions and replies instantly.
Decision 02
Ask, don't filter
- Why
- Managers want answers, not a maze of filters and tabs.
- What I did
- An “Ask Elara” bar with suggested questions sits right under the headline score.
Decision 03
Show where scores slip
- Why
- A list of numbers hides patterns across months and attributes.
- What I did
- A colour‑coded heat map shows, month by month, exactly where the experience drops.
05 · The screens
A website and a dashboard
Building an AI product?
- I make new, complex ideas easy to understand in the first scroll.
- Dashboards that answer questions, not just show charts.
- AI that feels human and on‑brand, so people trust it.
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