Taking many pills and supplements, they built an AI health tracker to spot
An eight-table Airtable health database, built with ChatGPT and Claude, that breaks down 10+ supplement labels down to proprietary blends.
This student was juggling many prescriptions and supplements and wanted to know whether too little or too much of something was behind their health issues. Instead of guessing, they used AI to turn label photos and lab PDFs into a structured personal health database. It is a clear example of how the program's AI skills can be pointed at a problem that matters deeply in one's own life.
Personal Health Tracker: Supplement Label Extraction & Airtable Database
Before
They were taking many prescriptions and supplements and could not tell what was causing their health issues. It might be a conflict, or too little or too much of something. The information lived on separate labels, PDFs and lab reports, with no single place to see it all together.
“Needed a way to determine what is causing my health issues and will taking many prescriptions and supplement, it might be a conflict of too little or too much.”
In their own words
The turning point
In the program they learned to hand AI tools real, messy material and ask for structured results. They gave ChatGPT copies of the labels for more than ten supplements and got back formatted CSVs of every ingredient, including those hidden inside proprietary blends. Then they used the 'Airtable PEARL Coach — Omni Prompt Builder' to write a prompt, and Claude built eight tables inside a new base called Personal Health Tracker.
“ChatGPT does a great job.”
In their own words
After
They now have a personal health database covering doctors, prescriptions, supplements, supplement ingredients, immunizations, health issues, lab results, and allergies and interactions. They built an ingredient analysis across everything they take, a lab consolidation skill that compares current and prior results and explains the changes, and kept local CSV copies so other tools can read the data. Their next step was asking Claude to build a health conflict checker using all of it.
What it lets people do
The tracker brings scattered medical paperwork into one place, so a person can see every ingredient they take, including what sits inside proprietary blends. It flags possible overlaps and conflicts and turns lab reports into side-by-side comparisons with plain explanations of each test and why a value may have changed.
What they learned
They learned that AI can do the tedious extraction work well, noting that ChatGPT does a great job reading labels into clean data. They also learned to work with the tools' limits, adjusting the plan when Claude could not create a new base directly, and to combine several tools into one system that serves a real personal need.
“Ask claude to build a health conflict checker using all of the above.”
In their own words
Personal Health Tracker: Supplement Label Extraction & Airtable Database was built during AI Mastery.
Read the full submission
Written 11 August 2026 Submitted by the storyteller
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