Gabriel AI UX/UI Design Enhancement

What is Gabriel AI?

Gabriel AI is a SaaS platform that uses AI to automate and personalize outbound voicemail campaigns, helping businesses communicate at scale while preserving a natural, human voice experience.

A Powerful Product That Was Hard to Understand

Gabriel AI offered advanced AI features like voice generation, smart sequencing, and campaign automation — but first-time users struggled to understand how these pieces fit together. The product surfaced functionality without clearly explaining why it mattered or when to use it, leading to hesitation and confusion. Without stronger guidance and context, users couldn’t quickly grasp the platform’s value.

Creating a campaign is the most important task in the product, yet the flow felt disorganized and unintuitive. Steps were unclear, progress wasn’t communicated, and users weren’t sure what would happen next. This disconnect between user expectations and the actual workflow created friction at the exact moment users needed confidence to move forward.

Because Gabriel AI operates in a space where users are cautious about AI, visual credibility mattered. However, inconsistent spacing, styling, and hierarchy across screens made the experience feel less polished and less reliable. Without a cohesive and professional design system, users were less likely to trust the product with something as personal as their voice.

How did I begin?

This project followed an iterative, feedback-driven design process focused on clarifying complex AI workflows while maintaining speed and feasibility within a startup environment. We began by auditing existing flows, identifying user pain points, and mapping the end-to-end user journey across both product and marketing surfaces. From there, I created low-fidelity wireframes to explore structure and flow, iterated through mid-fidelity prototypes based on internal feedback, and finalized high-fidelity designs aligned with brand and engineering constraints.

Throughout the internship, design decisions were continuously refined through team critiques and stakeholder feedback, allowing us to balance user needs with technical practicality. This approach ensured improvements were not only thoughtful, but also realistic to implement and scale.

Re-structured the campaign flow Organized campaign creation into clear, sequential steps that match user expectations and mental models

Improved progress visibility Introduced a more informative progress bar to communicate what’s completed, what’s next, and what’s required

Embedded voice control and playback Added voice adjustment and playback directly into message creation so users could hear and refine their voicemail in context

Added a “How It Works” section Introduced a step-by-step explanation of the product to immediately ground users in what Gabriel AI does and how it works

Reorganized information architecture Restructured sections to follow industry-standard patterns, improving scannability and comprehension

Refined UX writing and tone Updated language to feel more empathetic, professional, and trustworthy—especially important for AI-driven tools

Unified visual system across screens Standardized spacing, typography, colors, and components to create a cohesive, polished experience

Simplified dense information Converted text-heavy sections into tables, visuals, and structured layouts for easier navigation and understanding

Improved analytics clarity Shifted analytics toward visual insights and added smart sequencing data to help users quickly assess campaign performance

This project reinforced my belief that strong design lives at the intersection of empathy, clarity, and practicality. Especially when working with AI-powered products, design must do more than look polished, it must build trust, reduce uncertainty, and guide users through complex decisions with confidence.