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Research-informed AI for clinics

Clearer information. More connected care.

PrepAId develops AI-assisted systems for patient preparation, communication and clinic workflows, informed by scientific research.

Built around clinic knowledge. Designed for human oversight.

Reviewed knowledgeHuman understandingClinical oversight

Good care needs
good connections.

A clinic’s knowledge is valuable only when people can find it, understand it and know what to do next. We build the systems around that journey.

01

Patient preparation

Make clinic-approved information easier to navigate before appointments and procedures, with clear references back to the source.

Before the appointment
02

Patient communication

Help people find answers to routine questions and recognise when a conversation with their care team is needed.

Between visits
03

Clinic workflows

Give questions a clear route to the appropriate person, with the context needed to review and respond.

Behind every interaction

Designed for the workflow.
Adapted to the specialty.

Fertility

Preparation and questions across a complex treatment journey. The focus of our PREP-AID prototype.

Dental clinics

Opportunities to clarify appointment preparation, treatment information and routes back to the dental team.

Specialist care

A starting point for systems shaped by each clinic’s documents, people and responsibilities.

The right information.
A clear route to a person.

We use AI to help patients navigate clinic-approved information and support question routing, with clear references, defined limits and human oversight.

Explore a patient question

Illustrative workflow. These examples explain the approach; they do not provide clinical advice.

Route / Information
“Where can I find my preparation instructions?”

Start with the clinic’s guide.

Find the matching approved document and show a reference the patient can open. Keep the answer within the information available.

Document referenceClinic preparation guide · relevant page
Development prototype

A project in fertility care

Preparation that stays
connected to the clinic.

An AI-assisted fertility-care prototype exploring how patients can navigate reviewed information before treatment, while keeping questions connected to the people responsible for care.

Explore the development notes
The prototype’s design
01

Clinic-approved documents

The starting point for patient information.

02

AI-assisted answers

Responses include references to source sections and pages.

03

A route back to staff

Questions can enter a human review workflow.

Knowledge / Understanding / Responsibility
Development notes and evidence status

What is documented

The project handover describes source retrieval, citations, rule-based checks, AI-assisted routing and a staff escalation queue. These are prototype design features.

What still needs evaluation

Software testing alone cannot establish clinical effectiveness. Patient understanding, workflow fit, escalation reliability and real-world outcomes require evaluation in the intended care setting.

PREP-AID project documentation, 2025. Experimental educational support under development; clinical effectiveness has not been established.

Trust needs
a method.

Healthcare technology earns trust through clarity, review and evidence from the setting where it will be used. These principles guide what we aim to build.

ResearchDesignEvaluation
01

Define the intended use

Agree on the task, the people it supports and the limits of automation.

02

Keep the source visible

Use reviewed information and make the basis of a response open to inspection.

03

Make oversight practical

Define who reviews a question, how it reaches them and what happens next.

04

Evaluate in context

Examine understanding, usability, risks and workflow impact with the intended users.

Research informing the approach

The people
behind PrepAId.

Our team brings together scientific and software development, reproductive medicine, human factors, and patient experience research.

Gayane Sedrakyan

Gayane Sedrakyan

Founder & Scientific/Technology Lead

AI, Educational Technology & Human-Centred Intelligent Systems

Gayane Arustamyan

Gayane Arustamyan

Clinical Lead, Reproductive Medicine

Clinical expertise, patient safety & clinical validation

Simone Borsci

Simone Borsci

Human Factors & Safety Advisor

Human factors, usability & safe technology adoption

Valeria Resendes Gomez

Valeria Resendes Gomez

Patient Experience Researcher

Patient-centred research & experience design

Ahmed Almuhandes

Ahmed Almuhandes

Junior Product & Software Developer (Intern)

Product development, integration & technical validation

Let’s make the
next step clearer.

A useful starting point is a question patients ask repeatedly, a preparation journey that causes confusion, or a handoff that needs clearer ownership.

Three questions to begin with

  1. Where do patients need more clarity?
  2. Which information does your team trust?
  3. What would a better workflow look like?