Streamlined Surveillance, Scalable Design —
A Desktop SaaS Platform Built to Perform
Role: Lead UX/UI Designer & Researcher
Platform: Desktop (Web Application)
Timeline: 6–12 months
Team: 5–7 team members (Product Owner, Developers, Data Scientists, QA)
Tools: Figma, Miro, Slack, JIRA
Overview
This AI-powered camera vision SaaS platform enables users to remotely monitor and analyze visual data in real time using a machine learning-driven interface. Designed for professionals in research-heavy industries, the platform provides advanced image detection, labeling, and data insight features through a streamlined web dashboard. Key use cases included tracking behavior patterns, identifying anomalies, and providing actionable intelligence based on AI-driven visual recognition.
I owned the end-to-end UX and UI process—from initial user research and competitor analysis to wireframing, prototyping, design system development, high-fidelity UI design, and developer handoff. My work included building user personas, journey maps, and conducting stakeholder workshops to align priorities. I collaborated closely with stakeholders, engineers, and data scientists to ensure the product was not only technically feasible but also intuitive and accessible. I also established scalable components within Figma to support rapid iteration and long-term growth, resulting in a fully responsive, user-centric desktop product that balanced complex AI outputs with a clean, digestible interface.
Photo Gallery
About the Client – Serket Technologies
This project was completed in collaboration with Serket Technologies, an agri-tech company focused on transforming livestock farming through artificial intelligence. Serket develops cutting-edge computer vision systems that help farmers monitor animal health, behavior, and welfare in real time—reducing antibiotic use, improving productivity, and creating more sustainable food systems.
As part of Serket’s core product team, I led the UX and UI efforts for their desktop AI camera monitoring platform. The platform allows users to observe livestock remotely, receive health alerts, and leverage behavioral analytics, all through a responsive, data-rich web dashboard. This SaaS solution is a major pillar in Serket’s mission to digitize livestock farming and empower better decisions on the farm through AI-driven insights.
By working directly with the product owner, developers, and machine learning engineers, I helped bring Serket’s vision to life—translating complex technology into a human-centered, intuitive interface for users in agriculture and animal health.
My Contributions
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Research & Discovery:
Led stakeholder interviews and worked with SMEs to define key user groups, workflows, and data visualization needs. Conducted competitor audits and created user personas to align with high-level goals.
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Information Architecture & UX Strategy:
Designed the entire user journey from onboarding to image data analysis. Built flow diagrams and user maps to identify friction points and optimize key interactions.
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Design System Creation:
Developed and maintained a custom design system from scratch tailored to the product’s specific needs. This system included scalable components, atomic patterns, and typography guidelines to ensure visual and functional consistency across the application.
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UI Design:
Created wireframes, mid- and high-fidelity mockups, and interactive prototypes in Figma. Emphasis was placed on accessibility, visual hierarchy, and the seamless display of complex data sets.
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Developer Collaboration & Handoff:
Maintained close collaboration with the dev team throughout the project lifecycle. Delivered clean, well-documented Figma files and supported implementation through weekly standups, QA design reviews, and async Loom walkthroughs.
Key Features
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AI-powered object and behavior detection
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Data labeling & visualization modules
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Real-time alerts and event tagging
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Configurable dashboards for multiple camera feeds
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Custom user roles and permission settings
UX Challenges & Pain Points
Designing a platform at the intersection of AI and agriculture came with a unique set of UX challenges that shaped the foundation of my approach. The complexity wasn’t just in the technology—it was in the people, the workflows, and the skepticism around adopting digital tools in a traditionally analog industry.
A Broad Range of Users with Varying Tech Comfort
The platform needed to work just as well for a farmer in the field as it did for a tech-savvy operations manager or data analyst. Some users were interacting with digital systems daily, while others had never used a cloud-based platform before. I built inclusive UX flows with clear entry points, streamlined pathways for essential tasks, and a UI that avoided jargon and clutter. Interactive elements were kept intentional and focused, ensuring core functions were easy to find and use—regardless of the user’s technical background.
Low Trust in "Smart Tech"
There was a clear mental barrier to overcome: many users feared the platform would be too "fancy," too smart, or simply not built for them. My job wasn’t just to design something beautiful—it was to make it approachable and trustworthy. I focused on making the experience feel grounded and supportive. The interface emphasized simplicity, used plain language, and gradually introduced complexity only when needed. I also designed fail-safes and visual cues to give users more control, reinforcing a sense of empowerment rather than dependence on the system.
High Data Volume, High Risk of Overwhelm
With camera feeds generating massive amounts of real-time and historical data, clarity was essential. I worked closely with stakeholders and engineers to determine what data needed to be front-and-center versus what could be tucked into secondary views. I used progressive disclosure, collapsible panels, and dashboard customization to prevent cognitive overload. The result was a layout that offered depth for power users, while still surfacing the most relevant insights for daily decision-making at a glance.
Rebuilding Trust Through Design
By revamping outdated features and introducing a clean, scalable design system, I was able to restore visual and functional consistency across the platform. This not only made the product easier to use—it also made it easier to trust. Every design decision was rooted in creating a smoother, more confident user experience for a population that had historically been underserved by enterprise tech.
Outcomes & Impact
My work on the AI Camera Vision Platform focused on revitalizing an existing product—bringing consistency, usability, and scalability to both the user experience and the underlying design infrastructure. By modernizing the interface and introducing a flexible design system, I helped position the platform for long-term success and greater user adoption.
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Revitalized Outdated UX: Updated legacy features with modern, accessible, and user-friendly designs, reducing friction and aligning the platform with current UI/UX standards.
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Design System Overhaul: Rebuilt and documented a scalable design system tailored to the product’s needs, improving consistency, accelerating dev handoff, and enabling smoother rollout of future features.
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Increased User Confidence Across Skill Levels: Designed intuitive flows and simplified complex data interactions to support both novice and expert users, resulting in fewer reported usability issues and quicker onboarding.
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Feature Expansion with User-Centered Design: Introduced new platform features based on user and stakeholder feedback—prioritizing clarity, flexibility, and task efficiency for different user roles.
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Improved Developer Collaboration: Delivered clean, component-driven Figma files with clear documentation, reducing back-and-forth during implementation and strengthening design-dev collaboration.
Reflections
This project pushed the boundaries of designing for AI-driven platforms. Balancing cutting-edge tech with user-friendly design required constant iteration, close communication with developers, and a deep understanding of the end user’s mental model. The custom design system I created became the visual backbone of the product, enabling faster scaling and smoother dev handoff.