Autonomé

• Platform: iOS, Android, Desktop
• Design system management: Supernova.io
• Product type: Consumer App, Enterprise Data Platform
• Design system: Material 3, Custom design system
• Design tools: Figma, Cursor, Antigravity
• Approach: Fully AI-driven workflows
• Core Technology: Distributed Ledger (DLT), Smart Contracts

People generate valuable health data every day through smartwatches, health apps, hospital visits. Data brokers take it through confusing terms and conditions. Patients get nothing. People with wearables get taken advantage of, and the data sits in a silo with Apple, Google, Samsung, etc, doing nothing.

Meanwhile, researchers, pharmaceutical companies and AI builders desperately need clean, long-term health data. Traditional methods like web scraping and opaque terms often operate in a grey area, likely breaching consent laws ( ‘surveillance capitalism’). The data they can acquire is often biased, incomplete, or ethically questionable. There is another way.

Autonomé sits in the middle. People (Sellers) get paid for their data. Buyers get compliant, continuous datasets. I was brought on as the sole product consultant to design how both sides of this marketplace actually work.

This is the way.

I am lead experience design consultant for Autonomé. There are staff designers handling branding and identity. I handle everything else: the end-to-end product experience across the consumer app, corporate portal, and data dashboards. It is a very hands-on role, switching between creating design artefacts such as service blueprints, bias prevention, conducting workshops (remotely), discovery, concepts, prototypes, and production-ready designs in Figma, or directly in Cursor/Antigravity.

The core tension is designing for two timelines at once. The consumer app needs to work now (Horizon 1) — earning patient trust, collecting data, paying users. But every decision I make also needs to support the future enterprise data marketplace (Horizon 2) without requiring a rebuild.

Day to day, this means:

• Designing user journeys that collect data simply while meeting strict legal standards for enterprise sales later
• Mapping system flows that show how corporate revenue funds user acquisition — making the business self-sustaining
• Planning how the product experience shifts as the client moves from small academic datasets to large corporate access passes
• Building the design system that scales across consumer, corporate, and internal tools — plus pitch decks for fundraising
• Designing onboarding for both sides: a simple, trust-building flow for patients and strict identity verification for corporate buyers
• Running actor mapping, causal loop diagrams, and user journeys to uncover how data and money flow through the system

• Onboarding — ID verification and clear, plain-language consent so data can be legally used
• Continuous tracking — Automatic smartwatch syncing plus quick weekly questions to build a three-year health history
• Value exchange — A transparent payment system so patients see exactly what they earn
• Enterprise portal (future) — A secure dashboard where researchers search anonymised patient cohorts

I use practical, human-centred methods. The goal is to build something that actually solves problems for chronically ill patients and corporate data scientists — not just a compliance tool.

• Observe, reflect, make — I talk directly to patients with rare diseases and medical researchers to find out what frustrates them. We build rough prototypes and test before committing to code.
• Cross-functional workshops — Healthcare regulation is complex. I run sessions with the client’s legal team and research partners so legal roadblocks become design features early, not late blockers.
• Outcome-driven goals — Instead of “improve sign-ups”, the goal is: A patient with multiple sclerosis can securely sell their data in under 10 minutes without reading complex legal jargon. This grounds engineering in a measurable human outcome.
• System maps and blueprints — I map revenue loops, data flows (phone → secure enterprise database), and parallel user journeys (patient daily habits alongside data scientist workflows) to keep design, engineering, and legal aligned.

• Two cultures, one product — Autonomé has a privacy-focused team and a sales-focused team. I used system maps to show how corporate sales fund the privacy work, then designed separate interfaces so neither side compromises. Shared database, completely different experiences.

• Three-year data gap — Enterprise buyers need three years of continuous data. If sellers churn, the product dies. I designed passive smartwatch syncing with only two minutes of weekly input, plus a clear payment screen so users see the direct financial benefit of staying.

• Bias in medical data — AI trained only on wealthy, tech-savvy users is dangerous. I turned this ethical goal into a product rule: the corporate portal safeguards against bias by limiting data access if the patient cohort doesn’t meet certain standards (think Segment bias).

• Hidden legal complexity — AU, SG, US (not EU) healthcare laws require intense consent flows that typically scare users off and inflate acquisition costs. I worked with a legal advisory to turn complex contracts into a step-by-step process in plain English.

• IP protection through partners — The client will use channel partners to sell data in the US, which creates IP risk. I designed a limited partner portal — they can search and close sales, but never access underlying code or identifiable user data.

• Lower acquisition cost — Streamlined sign-up and ID verification. Less friction means more completions and better marketing ROI.
• Higher patient retention — Clear payment screens and simple consent forms build trust. Trust builds the long-term data history the enterprise side needs.
• Corporate renewal — The enterprise portal mirrors how data scientists actually work. If it saves them time, they renew.
• Privacy & Ethics, built in — Vision, mission on ethics and privacy and baked into process and workflows, but importantly, into the hiring process for all teams. Trust building starts internally and extends outwards.

Finalising accessibility standards for the consumer app so (almost) anyone can use it regardless of tech literacy. Simultaneously testing early enterprise portal designs with APAC & US-based medical research partners.