Supplement interactions with training and racing loads, electrolyte protocols, and caffeine-heavy pre-workouts are genuinely under-represented in standard clinical and pharmacological databases.
Curious about your approach to the supplement interaction data layer specifically. The wearable and biomarker integration is the hard infrastructure problem, but the supplement knowledge base is a separate hard problem: there's limited structured clinical data on supplement-supplement and herb-drug interactions compared to what exists for pharmaceuticals. Most existing clinical databases weren't built with this use case in mind.
I've been building vital-stack.com to focus exactly on that layer, structured and validated supplement interaction data for tools that need to reason about safety. Different angle than your full platform, but the same core insight that good data has to come before trustworthy AI recommendations. Happy to compare notes on sourcing if useful.
Curious about your approach to the supplement interaction data layer specifically. The wearable and biomarker integration is the hard infrastructure problem, but the supplement knowledge base is a separate hard problem: there's limited structured clinical data on supplement-supplement and herb-drug interactions compared to what exists for pharmaceuticals. Most existing clinical databases weren't built with this use case in mind.
I've been building vital-stack.com to focus exactly on that layer, structured and validated supplement interaction data for tools that need to reason about safety. Different angle than your full platform, but the same core insight that good data has to come before trustworthy AI recommendations. Happy to compare notes on sourcing if useful.