Healthcare, Rebuilt Around AI

I led Raiqa Health from concept to launch — shaping the patient experience, practitioner platform and AI-assisted workflows across clinical documentation, knowledge, reception and practice operations.

I also worked directly in implementation using Claude Code and Cursor, moving between Figma, front-end code and agent logic rather than treating design and build as separate stages.

0→1 product · Patient + practitioner ecosystem · AI-native healthcare

Project snapshot

The challenge

AI was easy to add. Designing healthcare around it was harder.

Patients needed a simple way to find and access care. Practitioners needed help with documentation, reception, knowledge and day-to-day administration.

AI could assist with all of these tasks — but healthcare introduced a more important question:

where should AI act, where should it assist, and where must a human remain in control?

The challenge wasn’t to put a chatbot inside a healthcare product. It was to design an ecosystem where specialised AI capabilities could become useful parts of real patient and practitioner workflows.

Why it was complex

Two sides of the same experience

Patient journeys and practitioner workflows were deeply connected. Appointments, communication and clinical activity needed to move coherently between both sides.

Different jobs needed different AI

Clinical documentation, knowledge retrieval, reception and supervision required different behaviours, context and levels of responsibility.

AI output wasn’t the final decision

Clinical workflows required practitioners to understand, review and act on AI-generated output rather than treating it as automatically correct.

From concept to working product

The work moved rapidly between product definition, UX, interaction design, AI behaviour and implementation as the product evolved from idea to launch.

My role

From product direction to working implementation.

I worked across product strategy, hands-on design, AI experience design and implementation — shaping both what the product should become and how it worked in practice.

Product Direction

Defined the product structure, priorities and experience across the patient and practitioner ecosystem.

Product Design

Designed patient journeys, practitioner workflows, information architecture, interactions and interfaces from early concepts through detailed product experiences.

AI Experience Design

Defined how specialised assistants participated in workflows, how their outputs were presented and where practitioner review and control were required.

Technical Prototyping & Build

Used Figma, Claude Code and Cursor alongside React and Tailwind to move directly from design into working front-end experiences and agent workflows.

Selected work

01 — One connected healthcare ecosystem

Connecting both sides of care.

Designed Raiqa Health and Raiqa Connect as parts of the same ecosystem — connecting patient discovery and access with practitioner workflows and practice operations.

Product Architecture Patient Journeys Practitioner UX

02 — Specialised agents, not one chatbot

Designing AI around specific jobs.

Structured the experience around specialised assistants for clinical documentation, knowledge, reception and supervision rather than asking one generic AI interface to do everything.

AI Interaction Design Agent Workflows Human-in-the-loop

03 — From Figma to working product

Closing the distance between design and implementation.

Moved directly between product design, front-end implementation and agent workflows using Figma, Claude Code, Cursor, React and Tailwind — allowing ideas to become testable product experiences quickly.

UX/UI Design Technical Prototyping AI-native Build

Impact at a glance

Connected ecosystem, not two products

Designed the patient and practitioner platforms around shared journeys rather than treating them as disconnected experiences.

Specialised AI with clear roles

Created distinct AI-assisted workflows for clinical documentation, knowledge, reception and supervision.

Humans stayed in control

Designed AI output to remain reviewable and actionable, keeping clinical judgement with practitioners.

Early evidence of operational impact

A single-practice pilot provided an early signal that AI-assisted workflows could materially reduce administrative burden while improving booking completion.

**

Early results from a single-practice pilot, not platform-wide performance.

Explore the products

Raiqa Connect

See the practitioner platform and AI-assisted practice workflows.

Raiqa Health

Explore the patient-facing healthcare experience.