
Client Success Story
AI-Powered Healthcare MVP: Patient Imaging Insights

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.
Healthcare
USA New York
6 months
$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.

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.
Project Interface Showcase
Client Testimonials
What Our Clients Say
Feedback on how our innovative solutions help achieve business results.

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
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
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
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
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
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
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
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
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
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
Related Work
Similar Cases

Mobile App
Social Media
AI/LLM
iOS
Beta
AI-Fashion Social Mobile App
A Berlin-based fashion social mobile app for enthusiasts to share outfits, discover styles, and interact through core social features with AI-powered tagging.

AI/ML
Cloud Infrastructure
AWS
ETL
Data Pipeline
Cloud-Based AI & ETL Platform for Agricultural Machine Learning
A cloud-native system capable of orchestrating AI workloads, managing data pipelines, and storing results for an AgriTech company specializing in machine learning for field crop analysis.

RAG
AI/ML
FinTech
SQL
Azure OpenAI
RAG-Powered Natural Language to SQL for Accounts Payable Automation
A proof of concept using RAG architecture to enable non-technical users to interact with accounting data through natural language queries translated into secure SQL.

RAG
FinTech
Process Automation
AI/ML
UK Compliance
RAG-Powered Process Automation for a Fintech Platform
A RAG-powered automation layer that enables teams to retrieve accurate information, automate internal workflows, and reduce manual processing across finance and operations.

SaaS
MarTech
Node.js
React
PostgreSQL
AI-powered SaaS Dashboard
A high-performance analytics platform that automates marketing reporting by aggregating data from major ad networks into a unified AI-driven intelligence hub.

Mobile App
Social Media
AI/LLM
iOS
Beta
A Berlin-based fashion social mobile app for enthusiasts to share outfits, discover styles, and interact through core social features with AI-powered tagging.

AI/ML
Cloud Infrastructure
AWS
ETL
Data Pipeline
Cloud-Based AI & ETL Platform for Agricultural Machine Learning
A cloud-native system capable of orchestrating AI workloads, managing data pipelines, and storing results for an AgriTech company specializing in machine learning for field crop analysis.

RAG
AI/ML
FinTech
SQL
Azure OpenAI
RAG-Powered Natural Language to SQL for Accounts Payable Automation
A proof of concept using RAG architecture to enable non-technical users to interact with accounting data through natural language queries translated into secure SQL.

RAG
FinTech
Process Automation
AI/ML
UK Compliance
RAG-Powered Process Automation for a Fintech Platform
A RAG-powered automation layer that enables teams to retrieve accurate information, automate internal workflows, and reduce manual processing across finance and operations.

SaaS
MarTech
Node.js
React
PostgreSQL
A high-performance analytics platform that automates marketing reporting by aggregating data from major ad networks into a unified AI-driven intelligence hub.

Don't wait — let's talk today.
Hi, I'm Danylo Melnychuk
CEO at Xedrum
Start Your Project
Looking for a reliable tech partner? We handle the technical implementation so you can focus on scaling your business.



