Tuluna

AI Health & Recovery Tracking for Active Women in Perimenopause

Brief

Tuluna was created to consolidate the growing complexity of perimenopause-related health information into a single structured experience. Cycle data, symptoms, sleep, training, supplements, medications, and cosmetic treatments often lived across multiple disconnected tools, making long-term tracking difficult and fragmented.

Over several iterations, Tuluna evolved from a personal experiment into a cohesive tracking platform focused on organisation, clarity, and reducing cognitive load.

Why Tuluna

Women navigating perimenopause often manage symptoms, training, hormonal treatments, supplements, and cosmetic procedures simultaneously. Existing tools required information to be spread across multiple apps, forcing users to manually reconstruct their history over time.

Tuluna aimed to centralise this information and create a clearer picture of what had happened and when.

My Role

Founder, Product Designer, UX Strategist and System Architect.

Tuluna began as a personal side project and became a hands-on exploration of AI-assisted product workflows. Using tools such as Base44, Claude Code, Stitch, Claude Design and Figma, I accelerated prototyping and component creation while maintaining ownership of product strategy, information architecture, interaction design and final visual execution.

What I did

Defined the product vision, information architecture, and tracking framework.
Led UX strategy, interaction design, and final UI design across multiple iterations.
Designed the logging flows, trend visualisations, treatment history, and navigation systems.
Directed the AI-assisted workflow across Base44, Claude Code, Stitch, Make, Claude Design, and Figma.
Built and refined the design system, component structure, and prototype experience.
Consolidated fragmented health and recovery information into a unified tracking experience.

Making Historical Patterns Easier to Understand

As the amount of information stored in Tuluna increased, reviewing changes over time became increasingly difficult. Early versions focused primarily on historical tracking and basic trend visualisation, but important information often remained buried inside separate sections of the app.

Over multiple iterations, the experience evolved to make long-term patterns easier to discover and navigate. Trend visibility improved, information became easier to access, and the hierarchy was refined to help users review their history without manually piecing together records across different categories.

The goal was not to provide recommendations, but to make historical information easier to understand and explore

Simplifying Logging

In early versions, logging actions lived directly on the homepage, creating visual clutter and increasing scrolling friction.

As more data types were added, the experience became increasingly difficult to scan. Symptoms and actions lacked clear organisation, creating unnecessary cognitive load.

Later iterations introduced dedicated spaces, structured categories, and quick actions that allowed users to access logging from anywhere in the product. Separating actions from content created more breathing room and improved overall clarity.

From Calendar Entries to Structured History

Early versions tightly coupled treatments to the calendar, making it difficult to review protocols over time or compare changes across months.

Subsequent iterations introduced a dedicated treatment history organised by category and date, allowing users to search, export, import, and attach notes to treatments.

By the final iteration, the focus shifted toward improving hierarchy and consistency within the wider design system.

The design system

As Tuluna evolved across increasingly complex flows, maintaining consistency and scalability became a core challenge. I developed a mobile-first design system with reusable components, structured tokens, interaction states, charts, and modular logging patterns that supported rapid iteration while keeping the experience coherent across the product.

The system was built through an AI-assisted workflow spanning Figma, Base44, Stitch, Claude Design, and Claude Code. These tools accelerated prototyping, component generation, and frontend implementation, while I retained ownership of the information architecture, interaction patterns, visual hierarchy, and final experience.

Building the design system allowed new screens and features to be introduced quickly without sacrificing consistency, making the product easier to evolve as requirements changed.

Design principles

Organize compelxity

Bring fragmented information into a single structured experience.

Reduce Cognitive Load

Simplify navigation and logging through categorisation, hierarchy, and reusable patterns.

Support Long-Term Tracking

Make historical records easier to search, review, and understand.

Results

Built and iterated across multiple generations of the product, evolving from exploratory concepts into a functional personal tracking platform.
Created a unified system for logging cycle data, symptoms, training, sleep, treatments, and cosmetic procedures.
Developed a scalable mobile-first design system supporting rapid iteration.
Explored AI-assisted workflows across design, prototyping, and frontend generation.
Most importantly, Tuluna revealed that organizing information solved only part of the problem. While historical tracking improved visibility, users still had to interpret what their data meant. This insight ultimately led to the creation of Peri, a separate recovery intelligence platform focused on capability and decision support.