Wellcura

3x Faster Patient Onboarding with an AI-Driven MVP for an Aussie Healthcare Startup

  • 93%

    Triage Completion

  • 3x

    Faster Patient Intake

  • 47%

    Less Manual Triage Time

  • 38%

    Improved Slot Utilisation

A fast-scaling digital healthcare startup in Sydney needed to remove operational friction from its virtual consultation workflow. Manual intake processes were slowing growth. We became a product engineering partner to help the Aussie startup with ideation, validation, and MVP product development to deliver an AI agent for faster patient onboarding.

  • Country

    Australia

  • Duration

    3 Months

  • Industry

    Healthcare

  • Services

    Idea & Validation Product Design Sprint Prototyping MVP Product Development AI Integration

  • Technologies

    TensorFlow React.js FastAPI LangChain OpenAI Models

planet-sec-title-arrow Problem Statement

  • Providers spent excessive time gathering routine patient information.
  • Patient drop-offs increased due to long registration flows.
  • Appointment slots were underutilised without structured triage.
  • The startup required scalable automation without compromising security.

planet-sec-title-arrow Challenges

  • Symptom descriptions were captured in inconsistent formats, making it difficult to categorise cases accurately or prepare doctors with a structured context.
  • Operational teams were stretched between intake coordination and clinical care, reducing efficiency during peak consultation hours.
  • The absence of a structured prioritisation system meant urgent cases could blend with routine bookings, affecting patient experience.
  • Deploying AI required strong privacy safeguards and secure data handling to maintain regulatory alignment and patient confidence.

planet-sec-title-arrow Solution

  • We conducted collaborative idea & validation workshops to map operational gaps and quantify how manual intake was impacting consultation throughput.
  • During the product design sprint, we defined a structured triage flow that balanced automation with clinical oversight to ensure patient safety.
  • Through rapid prototyping, we tested conversational prompts and symptom categorisation logic to refine clarity, reduce confusion, and minimise drop-offs.
  • In the MVP development phase, we built an AI-enabled intake assistant that translated patient responses into structured summaries ready for clinical review.
  • The AI integration ensured these summaries were automatically attached to each booking, allowing doctors to focus on diagnosis rather than data collection.
  • The system was deployed within a secure and scalable cloud environment, built to support future feature expansion and growing consultation volumes.

planet-sec-title-arrow Result

From concept shaping to AI-driven MVP rollout, we worked alongside the client to turn ambition into tangible outcomes.

  • 93% completion rate for AI-guided intake sessions.
  • The intake process became three times faster.
  • Manual triage time reduced by 47%.
  • Provider slot utilisation improved by 38%.

AI MVP improved patient onboarding & triage agent, automated queries, and structured patient data.

AI-driven insights & summaries improved efficiency in patient consulting without adding tools.

Reduced work overload by offloading admin queries to AI-driven customer support boosted operational efficiency.

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