Case Study
Here's the Case-Study of some of our works we'd like you to see...
AyuArc
AyuArc is an AI-powered personal health assistant designed to help individuals and families better understand their health by transforming fragmented data into structured, timeline-based insights. The platform consolidates symptoms, medical reports, and daily lifestyle information into a unified view, enabling users to track health patterns and gain meaningful, easy-to-understand insights through a secure and privacy-first system.
The Challenge
Patients and families faced multiple challenges in managing and understanding health data:
- Health information was scattered across symptoms, medical reports, and daily routines with no unified view.
- Medical reports were complex and difficult for non-experts to interpret.
- Existing systems lacked meaningful correlations between lifestyle factors (sleep, stress, habits) and symptoms.
- Families needed to manage multiple member profiles with strict privacy and data isolation.
- Users could upload outdated, incorrect, or irrelevant medical documents, reducing data reliability.
The Solution
AyuArc addressed these challenges using an AI-driven and privacy-first architecture:
- Built using Google Gemini with a secure Flask and PostgreSQL backend for intelligent health analysis.
- Converts unstructured medical reports into simplified, plain-language insights.
- Organizes symptoms, reports, and routines into a timeline-based health view.
- Correlates lifestyle factors such as sleep and stress with symptom patterns.
- AI validates uploaded documents by verifying the correct family member, report dates, and medical relevance.
- Sensitive personal information is masked before AI processing to ensure complete data privacy.
- Family-centric design ensures secure access and strict data isolation for each member.
AyuArc provides a clear and organized view of personal and family health by connecting symptoms, reports, and lifestyle patterns over time. The platform improves health awareness, simplifies medical information, and enables better long-term monitoring through a scalable and secure AI-driven architecture, empowering users while supporting, not replacing, healthcare professionals.
Technology Stack
