AyuArc - AI-Powered Personal Health Assistant
Flask
PostgreSQL
Google GeminiOCR
PythonAbout 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.
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 — empowering users while supporting, not replacing, healthcare professionals.
Our Approach
Challenge & Solution
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families needed to manage multiple member profiles with strict privacy and data isolation; and users could upload outdated, incorrect, or irrelevant medical documents, reducing data reliability.
Our Solution
AyuArc addressed these challenges using an AI-driven, privacy-first architecture: built using Google Gemini with a secure Flask and PostgreSQL backend for intelligent health analysis. The platform converts unstructured medical reports into simplified, plain-language insights, organizes symptoms, reports, and routines into a timeline-based health view, and 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, with family-centric design ensuring secure access and strict data isolation for each member.
What We Built
Key Features
AI-powered health analysis using Google Gemini
Timeline-based view of symptoms, reports, and routines
Lifestyle and symptom correlation engine
Document validation for correct member and medical relevance
PII masking before AI processing
Family profiles with strict data isolation
Impact
Results & Outcomes
Fragmented health data unified into a single timeline view
Medical reports converted to plain-language insights
Lifestyle-symptom correlations surfaced automatically
Privacy-first: PII masked before AI processing
Stack
Technologies Used
Flask
PostgreSQL
Google GeminiOCR
PythonClient
AyuArc
Industry
Healthcare / Health Tech
Technologies
Flask, PostgreSQL, Google Gemini…
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