HIA (Health Insights Agent)
Other
Open-source AI agent that analyzes blood-report PDFs and returns personalized health insights, with authentication and analysis history.
HIA (Health Insights Agent) is an open-source Streamlit app that lets users upload blood report PDFs and receive AI-generated, personalized health insights. It uses an agent-based architecture with a multi-model cascade via Groq for reliability, performs PDF validation and text extraction (up to 20MB), and supports secure user authentication plus session history for tracking past analyses. The project is built around a practical “report → extraction → analysis → insights” workflow and is designed to be deployable with Supabase (DB + Auth) and simple Streamlit configuration.
Industry: Other
Pricing: free
Use cases: clinicians, health coaches, nutritionists, biohackers, patients, caregivers
Capabilities: Summarizing blood test reports into plain-language insights and next-step discussion points., Automating extraction + analysis from uploaded medical-report PDFs (with validation and size limits)., Building a health-report analysis workflow with auth, persistence, and analysis history using Supabase., Using a multi-model fallback strategy (Groq-hosted Llama family models) to improve robustness.
Tags: health, blood report, pdf analysis, streamlit, supabase, supabase-auth, groq, llama, agent architecture, model fallback
- Is HIA completely free to use?
- Can HIA analyze blood report PDFs for insights?
- What is the maximum PDF size HIA can process?
- Does HIA have any health data certifications?
- Are there any region-specific availability limitations?

HIA (Health Insights Agent)
Open-source AI agent that analyzes blood-report PDFs and returns personalized health insights, with authentication and analysis history.
About
HIA (Health Insights Agent) is an open-source Streamlit app that lets users upload blood report PDFs and receive AI-generated, personalized health insights. It uses an agent-based architecture with a multi-model cascade via Groq for reliability, performs PDF validation and text extraction (up to 20MB), and supports secure user authentication plus session history for tracking past analyses. The project is built around a practical “report → extraction → analysis → insights” workflow and is designed to be deployable with Supabase (DB + Auth) and simple Streamlit configuration.
Key Capabilities
- Summarizing blood test reports into plain-language insights and next-step discussion points.
- Automating extraction + analysis from uploaded medical-report PDFs (with validation and size limits).
- Building a health-report analysis workflow with auth, persistence, and analysis history using Supabase.
- Using a multi-model fallback strategy (Groq-hosted Llama family models) to improve robustness.
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