Creative Direction
Logo Exploration
English Wordmark
Brand Guidelines
Mobile App
SaaS Platform
GUI
Controller Design
3D Product Designs
Motion Graphics
Booklet & Materials
User Manual
Kisui Story Campaign Videos
Promotional Videos
Tutorial Videos
Additional Content
2 Websites
CMS
Overview: MyNojo
I led the strategic planning, design, and launch of Kisui’s AI Smart-Farming platform, MyNojo. The app expanded the utility of Kisui’s Adam robots, created new revenue streams through partnerships, subscriptions, and e-commerce, and helped position the company beyond hardware sales. By introducing software offerings, we attracted partners and investors interested in scalable, AI-driven agricultural solutions.
I led the strategic planning, design, and launch of Kisui’s AI Smart-Farming platform, MyNojo. The app expanded the utility of Kisui’s Adam robots, created new revenue streams through partnerships, subscriptions, and e-commerce, and helped position the company beyond hardware sales. By introducing software offerings, we attracted partners and investors interested in scalable, AI-driven agricultural solutions.
My Design Approach
Every product and context is unique, so my design process is fluid and adapts to fit the context. My goal is to stay curious, collaborative, and iterative—an ongoing conversation between user needs, business goals, and what’s technically possible. Each step informs and reshapes the next as new insights emerge:
Determine the problem (or user need)
I begin by listening—to users, stakeholders, and data. I uncover challenges and opportunities and see how those align with user needs and business objectives.
Clarify and focus
Next I distill those insights and identify what’s most valuable to solve and where we can make the biggest impact. The goal is to define scope, align expectations, and ensure we are solving the right problem.
Explore and Iterate
I sketch, prototype, and share ideas early. Iterating often leads to the best results. Feedback is constant—from users, teammates, and stakeholders—so design evolves rapidly, exploring multiple directions before refining the strongest solutions
Execute and evolve
Once direction is validated, I develop the design system, collaborate closely with engineering for build alignment, and lead QA and usability testing to ensure quality. Feedback loops remain active even after launch to support ongoing improvement.
Discover
Before designing, I mapped the problems worth solving for both the business and end users. I interviewed leadership to understand revenue and growth goals, and spent time with farmers to capture their workflows, frustrations, and expectations of AI assistance. This dual approach ensured that product decisions addressed real-world challenges while advancing Kisui’s commercial ambitions.
By framing business and human questions together, we created a shared purpose statement that guided feature prioritization. This statement aligned leadership and design teams and served as a compass for all subsequent product decisions.
Research
By framing business and human questions together, we created a shared purpose statement that guided feature prioritization. This statement aligned leadership and design teams and served as a compass for all subsequent product decisions.
I organized research methods using an IDT chart, prioritizing ethnographies and user interviews to gain rich context. Joining field visits to orchards, I conducted contextual inquiries to understand how farmers interacted with robots, managed tasks, and made decisions in daily workflows. These observations revealed pain points and opportunities that surveys alone could not uncover.
Insights into Features
Research insights directly informed the MVP. The Pesticide eShop addressed difficulties farmers faced in finding approved pesticides online while creating a new revenue stream. The Logs feature simplified daily task tracking, providing immediate value and easing adoption of advanced features.
Research insights directly informed the MVP. The Pesticide eShop addressed difficulties farmers faced in finding approved pesticides online while creating a new revenue stream. The Logs feature simplified daily task tracking, providing immediate value and easing adoption of advanced features.
Define & Plan
These insights shaped the feature roadmap, balancing low-effort, high-impact tools like weather and humidity tracking with longer-term differentiators such as pest monitoring and foliage analysis. This approach ensured both immediate utility and future scalability.
MVP planning followed a phased approach: Alpha launch tested core functionality, Beta expanded features and adoption, and a long-term roadmap outlined advanced capabilities, App Store deployment, and paid-tier services.
Iteration & Prototyping
MVP planning followed a phased approach: Alpha launch tested core functionality, Beta expanded features and adoption, and a long-term roadmap outlined advanced capabilities, App Store deployment, and paid-tier services.
I led rapid prototyping, testing, and iteration of dashboards, AI features, and workflows with farmers and engineers. Feedback loops enabled continuous improvement and clarified interactions, microcopy, and visualizations.
Design System
Data flows from Adam sensors, weather inputs, and user logs were translated into actionable dashboards. Prioritizing clarity and interpretability ensured farmers could make practical decisions quickly without being overwhelmed by raw data.
I created a modular, token-based design system for web and mobile, standardizing components, typography, and colors for scalable implementation.
Delivery
Post-launch iterations refined dashboards, AI recommendations, and workflows, ensuring immediate utility while preparing for advanced features and future scalability.
Data visualization choices were informed by research on map-based interfaces and drone imagery, integrating robot sensors, weather APIs, and user-entered logs to display key metrics effectively on home and detail screens.
Feedback
The design system was fully integrated post-launch, interface behaviors refined, and user feedback mechanisms implemented.
Monitoring and iterative updates improved onboarding, dashboards, and core features, laying the groundwork for Beta testing and advanced AI-driven enhancements.
