Vista

A modern eye-care app that helps users track vision health and access personalized tips for better eyesight.

I led product discovery and UX architecture for a B2B AIaaS platform, translating a technical proof of concept into a clearer, enterprise-ready V1 product structure.

I led product discovery and UX architecture for a B2B AIaaS platform, translating a technical proof of concept into a clearer, enterprise-ready V1 product structure.

I led product discovery and UX architecture for a B2B AIaaS platform, translating a technical proof of concept into a clearer, enterprise-ready V1 product structure.

Industry

B2B AIaaS · Enterprise SaaS

Role

Health · Digital Solutions

Team

Designer-Led Team (3D · 1PO · 2TPM · 3AI Sci · 2BE)

Duration

3 months

Context

Vista’s first version lacked clarity and consistency, making it hard for users to track their vision health effectively. Navigation felt fragmented, and important features like checkup reminders or progress logs were hidden.

Users needed a simple, trustworthy app that makes vision care easy and accessible — not overwhelming. The brand required a fresh identity to match its mission of supporting long-term eye health.

Core Product Challenges

Three constraints prevented the POC from operating as an enterprise product

The challenge was not visual consistency alone. The platform needed a product model that connected modules, workspaces, permissions, and system feedback into one understandable experience.

Three product-level constraints shaped the redesign:

  1. Fragmented AI Modules
    AI capabilities existed as isolated functions without a shared workflow, making it difficult to understand how modules connected or what users should do next.

  2. Undefined Multi-tenant Structure
    Workspace, role, and permission concepts lacked a clear product model, limiting the platform’s ability to support enterprise collaboration.

  3. Low Visibility During AI Operations
    Long-running AI tasks provided limited feedback about progress, system status, and possible next actions.

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Discovery

The redesign focused on creating a calm, user-friendly app that builds trust while providing practical tools for vision tracking.

We aimed to deliver a seamless experience where users can monitor eyesight changes, get personalized recommendations, and manage appointments with confidence.

A platform-wide heuristic review surfaced 43 experience and architecture gaps. Affinity mapping turned those findings into four product priorities, creating a roadmap that connected immediate usability fixes to longer-term platform structure.

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Top Heuristic Violations

43

Audited gaps mapped across Nielsen's heuristics.

Consistency & Standards — 35% (15 items)

Visibility of System Status — 20% (9 items)

Efficiency & Flexibility — 16% (7 items)

User Control & Freedom — 14% (6 items)

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Product Decisions

We built a modern, wellness-inspired interface with clear typography, soothing colors, and intuitive navigation.

From progress dashboards to appointment scheduling, every feature was streamlined into a cohesive flow — turning Vista into a reliable everyday companion for better eye health.

Impact

A clearer foundation for an enterprise AI platform

This work moved Vyin from a collection of technical capabilities toward a more coherent product model. It established shared priorities for module structure, workspace architecture, system feedback, and reusable interaction patterns. Because validated adoption and business metrics were unavailable, the outcome is presented as a product and delivery foundation rather than quantified impact.

Reflection

AI product design is an architecture problem before it is a UI problem

The central challenge was turning fragmented technical capabilities into a product experience that people could understand, trust, and scale. Working across discovery, UX architecture, interaction design, and delivery strengthened my ability to connect technical constraints with product decisions. Evidence that would strengthen this case further includes post-release usage signals, task-level usability findings, and stakeholder or customer feedback when those become available.

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Steven Li

Product Designer · AI / SaaS / Enterprise

Interested in how I approach complex product problems?

I turn ambiguity into structured product decisions and scalable experiences.

© ZhenXi Li 2026 | All Rights Reserved

Steven Li

Product Designer · AI / SaaS / Enterprise

Behance icon
linkedin icon
Interested in how I approach complex product problems?

I turn ambiguity into structured product decisions and scalable experiences.

© ZhenXi Li 2026 | All Rights Reserved

Interested in how I approach complex product problems?

I turn ambiguity into structured product decisions and scalable experiences.

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