I led UX/UI design for svEye, creating intuitive interfaces for a complex data environment where unstructured news becomes actionable risk intelligence.
Semantic Visions needed a product designer to shape svEye from concept to reality. The platform would use AI to analyze vast volumes of global news, detecting risks and surfacing intelligence for analysts and decision-makers. But the challenge wasn’t just “make it look good” — it was making a deeply complex data product feel approachable and useful.
This was ground-up design — defining the information architecture, interaction patterns, and visual language from scratch.
Users would be configuring AI-powered searches, reviewing multi-dimensional reports, and comparing entities. The interface needed to handle density without overwhelm.
The product needed a component system that could grow with it — supporting light/dark themes, multiple states, and accessibility from day one.
The business model required contextual upgrade prompts that informed users of plan limits without disrupting their workflow or eroding trust.
Over 18 months, I shaped svEye across four interconnected areas — each requiring deep UX thinking and close collaboration with product and engineering.
I built a flexible design system with reusable, multi-state components — buttons, menus, panels, modals, and more — all supporting light and dark mode with accessibility built in. The component library ensured visual consistency as new features were added and gave the engineering team a reliable reference for implementation.
When I handed off the project, the incoming designer and dev team had a complete, documented system to build on — not a collection of one-off screens.
I designed and established the product's key multi-step processes from scratch: search configuration, report building, CSV entity upload, and automation flows. Each was structured as a guided experience with contextual controls, clear validation states, and progressive disclosure. The user flow below is one example of how I mapped these end-to-end.
This approach — designing every state, edge case, and transition deliberately — reduced friction, improved discoverability, and encouraged deeper exploration across the platform.
This flow illustrates how I approached multi-state design across the product — mapping every path from default to error to resolution. Each workflow was designed with the same rigor.
I structured the product around a modular dashboard framework where users configure searches, review intelligence reports, and compare entities — all in one environment. The interface supports multiple views (charts, tables, detailed parameters), filterable data, and comparative analysis across entities.
Analysts could go from question to insight without context-switching between tools. The modular approach meant new visualization types could be added without redesigning the layout.
I designed contextual PLG nudges that surfaced at the moment users hit plan limitations — not as aggressive upsells, but as informative prompts explaining what they could unlock. These appeared within the flows users were already in so they felt like part of the product rather than marketing interruptions.
These prompts supported business revenue goals while maintaining user trust. The design had to walk a fine line between being visible enough to drive upgrades and subtle enough not to frustrate users.
Over 18 months, I took svEye from early concept to a complete MVP ready for soft launch. The product I delivered included a full design system with documented components, multi-theme support, and developer handoff materials that enabled Semantic Visions to transition design work in-house with confidence.
What started as a blank canvas became a scalable, analyst-friendly platform — with thoughtful data workflows, modular dashboards, and growth mechanics woven into the experience from the foundation up.
Before any screens were designed, I contributed to defining the product vision. This included mapping features and constraints, creating user flow diagrams, and conducting competitive analysis of existing dashboards and intelligence tools.
He is able to take clear requirements and come up with a solution far superior to what was originally expected.
I had the pleasure of working with Shawn for over a year and a half on a B2B data and analytics product. Shawn is extremely diligent and dedicated to his work, as well as reliable and always looking for ways to improve. He saw the product through from ideation in the very early discovery phase to a full-fledged MVP and was an integral part of that journey.
As a designer, Shawn is detail-oriented, creative, and has quite a talent for thinking outside the box. He is also able to work with a concept in its early stage, always encouraging his colleagues to think about what exactly we want to achieve for our users and why. As a Product Manager, I knew I could rely on him to always come up with something better, or a better approach.
I design and build products from concept to launch. Let’s talk about what you’re working on.
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