Mars Pet Care Digital Tools - Greenies Toothscan






IAMS Poopscan






Royal Canin Kitten Weightcheck
Anicura Dermscan
VCA Pawscan






Cocoascan


Deliverables
Product Architecture
Product UX/UI
Brand Design Systems
AI Generated Assets
Illustration
Details
The Challenge
MARS Pet Care had developed multiple AI - powered diagnostic models for pet health - spanning oral health, skin conditions,
digestive issues, and beyond. However, each tool was being built in isolation across different brands and divisions
(Pedigree, Royal Canin, Mars Veterinary Health, Science & Diagnostics), creating inconsistent user experiences,
duplicated effort, and no path to scale globally. The VP of Innovation needed a unified platform that could productize
these AI instruments while maintaining brand flexibility and regulatory compliance across markets.
My Role + Approach
As Lead Product Designer embedded within MARS's Digital Health team, I helped to architect and design the Digital Health Platform - a
modular design system and SDK that enables rapid development of AI-powered health instruments for both pet parents and
veterinarians across the entire MARS ecosystem.
Platform Architecture Design: I designed a component-based system that allows any AI diagnostic tool to be configured
for different brands, markets, and use cases without rebuilding from scratch. This included creating reusable UI patterns,
establishing design governance processes, and developing a library of approved components that enable creative flexibility.
Multi-Brand Design System: I built design systems that work seamlessly across MARS's diverse brand portfolio - from consumer-facing apps
(Greenies, IAMS, myVCA) to veterinary diagnostic tools to third-party retailers (Walmart, Amazon). The system maintains
brand identity while ensuring consistent, accessible user experiences.
0-to-1 Product Development: Led design sprints to launch eight (and growing) AI-powered diagnostic tools from concept to market:
- Toothcheck
- Toothscan (oral health screening)
- Pawscan (paw pad health assessment)
- Dog Dermascan (skin condition detection)
- Puppy Weightcheck
- Kitten Weightcheck
- Poopscan
- Cocoascan (cocoa pod disease detection for 3rd party agricultural use)
Each tool uses computer vision models to detect visual indicators of disease, with configurable front-end and back-end architecture
that scales across all health territories.
Impact & Results
Speed to Market:
The platform reduced time-to-launch for new AI diagnostic tools from years to months. All four MARS divisions (PN, RC, MVH, SDX)
deployed the same Toothscan product experience, configured to their specific brand and business requirements, demonstrating true
platform scalability.
Adoption at Scale:
Toothscan has scanned over 30,000 teeth to date, with consumer-facing tools driving measurable KPIs
including appointment bookings, nutrition recommendations, and product purchases - all tracked directly within the platform.
Global Extensibility:
The platform now powers diagnostic tools across consumer websites, mobile apps, veterinary portals,
and third-party platforms globally (Europe/Asia). The component-based design system and “Call to Action” structure scale
across languages, markets, and regulatory requirements.
Innovation Unlock:
By creating reusable foundations, the platform enabled MARS to extend beyond pet health into adjacent markets (Cocoascan for cocoa pod disease detection), proving the architecture's flexibility for productizing AI across diverse use cases.
Key Design Contributions
- Platform architecture and information design for multi-brand, multi-product ecosystem
- Design system governance ensuring compliance and consistency across 4 global divisions
- MARS brand asset creation (internal + go-to-market)
- Strategic design leadership bridging needs of R&D, brand and development teams
Key Highlights
- Digital Health Products Live at Petcare: 8
- MARS divisions using Digital Health Products: 4
- MARS brands using Digital Health Products: 10
- Digital Health Products globally deployed in: 27 Markets















