Client Success Story

AI-Powered Healthcare MVP: Patient Imaging Insights

Screenshot of the AI-Powered Healthcare MVP for Patient Imaging Insights project interface

Project Overview

Empowering Patients through AI-Driven Clarity

A New York-based healthcare MVP that helps patients better understand their medical imaging results through AI-assisted explanations in plain, human-readable language.

Industry:

Healthcare

Location:

USA New York

Duration:

6 months

Budget:

$35K

Strategy & Execution

Our HIPAA-Aware AI Architecture & RAG Implementation

We treated this project as both a healthcare MVP and an AI product foundation, even though AI was not intended to be a final diagnostic authority.

Our approach focused on: Building a HIPAA-aware AI architecture, ensuring secure handling of PHI, encrypted data storage, controlled access, and audit-ready workflows.

Implementing a RAG architecture, allowing AI responses to be grounded in verified medical sources, guidelines, and structured knowledge rather than raw model output.

Creating an MVP that could quickly validate user demand with real patients.

Preparing the system for clinician-in-the-loop workflows, future clinical partnerships, and deeper AI validation.

Instead of starting with heavy AI training or custom medical models, we focused on practical AI integration, strong prompt orchestration, and reliable workflows that could evolve over time.

The Gap in Patient Imaging Interpretation

Patients regularly receive medical imaging results that are: Hard to understand without medical training, Delivered with minimal explanation, Stress-inducing and unclear, especially outside clinic hours.

From the business side, the founder faced several challenges: Doctors and clinics don't have time to answer repetitive patient questions, Building a healthcare product requires careful compliance and wording, Overpromising AI capabilities could create legal and trust risks, Speed mattered more than building a 'perfect' AI model from day one.

The challenge was to balance AI usefulness with healthcare responsibility, while still delivering a compelling consumer experience.

Interface screenshot demonstrating Healthcare MVP with AI-Assisted Insights features

Healthcare MVP with AI-Assisted Insights

We delivered a Healthcare MVP with AI-assisted insights, designed for clarity, safety, and future expansion.

KEY FEATURES IMPLEMENTED:

  • 01

    AI-Assisted Image Explanation

    Patients can upload X-rays or other medical images. The AI provides educational explanations in simple language, focusing on general observations and common patterns, always framed as informational and not diagnostic.

  • 02

    Smart Context Layer

    Users can add context such as symptoms or doctor notes. AI uses this input to tailor explanations and highlight what questions patients may want to ask their physician.

  • 03

    Medical-Safe AI Prompting

    We implemented a carefully structured AI layer that avoids diagnosis or treatment advice, uses disclaimers and healthcare-safe language, and prioritizes clarity over certainty. This made the AI useful while remaining compliant and trustworthy.

  • 04

    Clean Patient-First UX

    The app was designed for non-technical users with simple upload flow, clear visual feedback, and human-friendly explanations instead of medical jargon.

  • 05

    Scalable & Compliant Architecture

    HIPAA-aware data handling, secure cloud infrastructure, and modular backend ready for future AI model upgrades or clinician dashboards.

Client Testimonials

What Our Clients Say

Feedback on how our innovative solutions help achieve business results.

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Xedrum delivered a production-ready AI-powered application within the agreed timeline and budget, including a working release on Apple TestFlight. The team was highly proactive in resolving issues, adapting to evolving requirements, and ensuring the AI functionality aligned with real user needs. Throughout the engagement, Xedrum consistently treated the project as a priority and demonstrated a strong understanding of both technical and business concerns.

Celine LeibfriedCEO at Unscripted
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Xedrum successfully implemented a robust system that allows users to upload data, execute automated jobs, and retrieve results efficiently. The team delivered all components on schedule, maintained clear communication through weekly and ad-hoc meetings, and demonstrated professionalism throughout. The final solution met both technical and operational expectations.

Tomer PeretzCTO at Osirix
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Xedrum's engineers worked closely with the client's project manager, integrating seamlessly into the existing workflow. The team consistently delivered planned milestones, maintained strong communication through regular online meetings, and brought a personal, collaborative approach that made them feel like an in-house AI team rather than an external vendor.

FredericCTO at Touch2Seen
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Xedrum operated as an extension of the client's internal team, taking ownership of both delivery and day-to-day execution. Their engineers quickly understood the product context, collaborated across time zones, and proactively contributed ideas to improve the solution. The team maintained consistent velocity, adapted to changing priorities, and helped move the product forward without adding management overhead.

Arnon ZamirCTO at Aristo
Clutch logo

Xedrum successfully implemented a robust system that allows users to upload data, execute automated jobs, and retrieve results efficiently. The team delivered all components on schedule, maintained clear communication through weekly and ad-hoc meetings, and demonstrated professionalism throughout. The final solution met both technical and operational expectations.

Richard BatesCEO at Acumen Data

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Hi, I'm Danylo Melnychuk

CEO at Xedrum

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