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Product Design · Mobile · AI Health Companion

Qetos: daily momentum

Qetos turns complex functional-medicine protocols into calm, time-aware daily actions through AI coaching, biometric context, and positive reinforcement.

9:41

Phase 2 · Rebuild · Day 18/30

Metabolic Resilience Protocol

Next best action

One 5-minute breathing reset.

🌿Stress · protects momentum
65

You're building momentum

Small, steady actions across your five pillars — no need to rush.

Your protocol path

🥑D · DietBuild a protein-forward lunch within your carb ceiling
72
🌙R · RestDim screens and begin wind-down by 9:30
60
🏃E · ExerciseTake a 20-minute walk after lunch
80

A calm daily path — one next best action, a gentle momentum read, and the five D.R.E.S.S. pillars as soft, time-aware cards.

Open the app previewInteractive concept prototype · generic demo data

Role

Lead Product Designer

Timeline

Summer 2026

Team

Design — Raúl Falcón

Type

Consumer Health · AI Companion

Qetos AI-powered health companion app

Overview

Helping users feel capable, not corrected

Functional medicine protocols are often clinically strong but difficult to sustain in daily life. Qetos fills that execution gap: an AI health companion that turns dense plans into calm, time-aware guidance.

Through research and iteration, Qetos evolved from a compliance prototype into a system focused on helping users feel capable, not corrected. As Lead Product Designer, I led strategy, UX research, interaction design, behavioral psychology, prototyping, and visual design.

Qetos makes complex health behavior feel manageable while creating structured adherence data for future clinical dashboards.

It’s the flagship product of Ailiur, the studio I’m building for AI-native tools across health, learning, and science — and the clearest expression of my through-line: turning complex scientific systems into something people can act on.

A user moving through their daily protocol inside the Qetos app
Qetos in use — guiding a patient through their protocol one time-aware action at a time.

Audience

Who Qetos is really for

Adherence is the make-or-break variable in metabolic health, so Qetos is designed for the three people who decide whether a protocol succeeds.

01

The patient

A functional-medicine patient holding a complex protocol — motivated, but overwhelmed and at daily risk of quitting. The primary user.

02

The clinician

Physicians and health teams who need real adherence signal between visits, not just lab archives — the future dashboard audience.

03

The metabolic-health space

Ketogenic and metabolic-psychiatry protocols (e.g. Metabolic Mind) where execution, not information, is the bottleneck.

The Problem

Clinical protocols are powerful — but hard to live with

Functional-medicine patients often receive complex protocols spanning diet, supplements, breathwork, sleep, movement, tracking, and symptom journaling. While clinically useful, these plans can become overwhelming in daily life.

In early testing, one health plan required 26 minutes of deep focus just to understand. Users had to figure out what mattered, when to act, how to prioritize, and what counted as progress.

The problem was not motivation. It was translation: patients lacked an interface to turn clinical complexity into daily behavior.

Decoding a dense clinical protocol by hand
Decoding a clinical protocol — users spent ~26 minutes just understanding a single plan before they could act on it.

26 min

Of deep focus to understand one optimal health plan (User Test v1)

10+

Daily interventions — diet, supplements, breathwork, recovery and tracking

Translation

The real barrier to adherence — not motivation

Key Early Insight

The protocol was not the product

The daily interpretation layer was the product. Qetos needed to become the missing behavioral interface between clinical instruction and real human follow-through.

How might we translate a medical protocolClinical protocol into a mobile experienceMobile product that leverages positive reinforcementReward, not guilt to drive long-term adherenceDaily follow-through?

Research

Understanding why users abandon health plans

I conducted multiple rounds of user interviews and playtesting sessions to understand how people actually respond to protocol-based health routines.

The research focused on three questions.

01

What makes a protocol feel overwhelming?

Users felt behind when the full plan appeared at once. Too many tasks made starting feel overwhelming.

02

What makes tracking feel negative?

Missed habits, red warnings, and failed streaks made users feel judged. Punitive tracking increased avoidance.

03

What makes users want to continue?

Users responded to wins, recovery, and momentum. They wanted effort recognized, not just perfect compliance.

Synthesizing user interview and playtest comments on sticky notes
Synthesizing interviews and playtest comments to map where the protocol broke down.
Playtesting a protocol routine with a user
Playtesting protocol routines to observe real, in-the-moment behavior.
Early design sketches exploring the daily interpretation layer
Sketching the daily interpretation layer — how a protocol becomes a sequence of small moments.

Comparative Research

The missing middle between trackers & medical portals

I mapped Qetos against two existing product categories to find the gap it needed to fill.

A generic habit tracker app
Generic habit trackers — great at streaks and reminders, but blind to clinical specificity, time-boxed interventions, and biometric nuance.
A clinical patient medical portal
Medical portals — strong at records and lab results, but they archive care rather than help patients execute it day to day.

Qetos sits in the missing middle — combining the motivational rhythm of a habit product with the seriousness and structure of a clinical protocol system.

The Initial Prototype

A strict adherence model that created the wrong emotion

The first prototype centered on compliance, showing tasks, progress, and missed actions clearly.

User feedback revealed the issue: rigid checklists and clinical warnings made people feel like they were failing.

Users needed a way to re-enter the protocol without guilt, not more reminders that they were behind.

An early Qetos build screen
Early build — a literal translation of the clinical plan into a checklist.
The initial punitive prototype flagging missed habits
The initial “punitive” prototype — missed tasks and red warnings triggered a shame loop in testing.
The central pivot: from compliance tracking to momentum design.

Design Strategy

Turn the protocol into a daily companion

The final product direction was built around three UX principles.

01

Progressive disclosure

Qetos breaks the protocol into time-boxed moments instead of showing everything at once. Users see the next relevant action — supplements, breathwork, logging, or recovery — only when it matters.

02

Positive reinforcement

Qetos turns adherence into a reward loop. Instead of emphasizing failure or missed tasks, it highlights wins, effort, and momentum.

03

Context-aware AI guidance

Qetos uses biometric and behavioral context to suggest one gentle next step, helping users act without being overwhelmed by raw health data.

The Qetos time-boxed carousel showing only the current window of action
Progressive disclosure — the time-boxed carousel surfaces only the current window of action.
Context-aware AI chat referencing biometric recovery stats
Context-aware guidance — the AI translates biometric and protocol context into one gentle next step.

Signature Interaction

The “Log a Victory” shift

Qetos replaces punitive check-offs with positive logging, helping users recognize small wins instead of missed tasks.

The “Log a Victory” modal became the product’s emotional core, shifting the tone from clinical monitoring to personal momentum.

The Log a Victory modal celebrating a behavioral win
The “Log a Victory” modal — celebrating wins like navigating a craving, instead of flagging misses.

Final Product

A calm AI health companion for daily adherence

The final Qetos prototype connects a set of mobile experiences — each one a small, low-friction moment in the day.

Qetos AI chat companion
AI Chat Companion — recommends the next best action based on recovery, symptoms, food, and goals.
Qetos meal recognition and logging
Meal Recognition — estimates macros, recognizes meals, and ties nutrition back to the protocol.
Qetos manual ketone logging
Manual Ketone Logging — a lightweight entry pattern for tracking metabolic state.
Qetos guided breathing reset
Guided Breathing Reset — a calming intervention for stress and nervous-system regulation.
Qetos recipes and protocol suggestions
Recipes & Protocol Suggestions — nutrition tuned to goals like LDL support and sustainable ketosis.
Qetos guided meditation experience
Guided Meditation — a recovery moment surfaced when biometric stress runs high.

Product System

A dual-sided product model

Qetos is a consumer mobile product designed with a future clinical backend in mind. Every logged meal, supplement, reading, reset, or behavioral win creates structured adherence data.

For patients, this means clarity and momentum. For clinicians, it becomes a dashboard layer for adherence, symptom trends, biometric patterns, and disengagement signals.

The same daily product creates both consumer value and clinical value.

B2C

Patient-facing mobile companion with daily adherence loop

B2B

Clinical dashboard layer — protocol adherence signals for physician teams

Dual model

One product, two revenue surfaces — consumer subscription + clinical SaaS

Technical Collaboration

Designed to be built

I was the solo designer, so technical collaboration here meant designing for engineering rather than alongside a team — making the system buildable, not just beautiful.

Every logged meal, supplement, reading, reset, and win is modeled as a structured event, so the consumer app and the future clinical backend share one schema instead of two. The AI guidance is scoped as a clean “context in → one action out” pattern that maps onto real biometric integrations (e.g. recovery data), and the flows are prototyped at high fidelity for an unambiguous handoff.

Before & After

From overload to agency

The clearest way to see the work is the shift in mental model — what changed between the first compliance prototype and the final companion.

DimensionCompliance prototype (v1)Momentum companion (final)
Mental modelA checklist to completeA daily companion that builds momentum
Emotional toneShame on a missed taskCelebrated wins — “Log a Victory”
Information loadThe whole plan, all at onceOne time-boxed action when it matters
Time to understand~26 minutes of deep focusGlanceable next step
Data producedTasks done / missedStructured adherence for clinicians

Impact & Learnings

From overload to agency

The product evolved through research, playtesting, and repeated iteration — from a rigid task tracker into a more human-centered AI health companion.

01

26 minutes → daily micro-actions

A dense clinical plan became a sequence of small, time-aware actions surfaced exactly when they matter.

02

Punitive tracking → positive reinforcement

The interface shifted away from failure states and toward behavioral wins, removing the shame loop that drove avoidance.

03

Static protocol → adaptive companion

Qetos evolved from a checklist into a contextual AI system that guides next steps while building adherence data for future clinical dashboards.

Live App Preview

See what a day inside Qetos feels like

The protocol becomes a calm daily path: one next best action, a gentle momentum read, and the five D.R.E.S.S. pillars as soft, time-aware cards — no checklists, no red warnings. Open the interactive prototype to move through Today, Chat, Logging, and Habits yourself.

Open the app previewInteractive concept prototype · generic demo data
9:41

Phase 2 · Rebuild · Day 18/30

Metabolic Resilience Protocol

Next best action

One 5-minute breathing reset.

🌿Stress · protects momentum
65

You're building momentum

Small, steady actions across your five pillars — no need to rush.

Your protocol path

🥑D · DietBuild a protein-forward lunch within your carb ceiling
72
🌙R · RestDim screens and begin wind-down by 9:30
60
🏃E · ExerciseTake a 20-minute walk after lunch
80
Qetos uses AI to make complex health routines feel manageable, guiding daily actions, rewarding progress, and creating adherence data for future care teams.

In Summary

The two-minute read

For recruiters & hiring teams

Lead product designer who took an AI health app from a flawed compliance prototype to a calm, behavior-first companion — owning research, behavioral UX, interaction, and high-fidelity UI solo. Turns a 26-minute clinical document into a sequence of small daily actions, and designs the data model so the consumer app feeds a future clinical dashboard.

For founders & operators

Sees the business in the design: architected Qetos as a dual-sided product (a B2C habit loop that generates B2B adherence data) from one daily experience, and located a real market gap — the “missing middle” in metabolic health — before drawing a single screen.