We launched Open Wearables on Product Hunt today. For teams building AI agents, coaches, or copilots in health, OW turns raw wearable streams into the structured, scored, time-series context an LLM can actually reason over.
Imagine this: Both devices on the same wrist, same night of sleep, same morning. One shows green, one shows red. And neither will tell you how it decided. That's not a hardware problem. It's an algorithm problem. Different weightings, different baseline calculations, different thresholds - all proprietary, all invisible. You're left choosing which black box feels more right today. The reason we open-sourced the scoring algorithms in Open Wearables wasn't just philosophical. It's because conflicting scores are meaningless without context, and context requires transparency. When you can see exactly how a Resilience Score weights HRV versus sleep duration versus resting heart rate, you can actually reason about the discrepancy. Has anyone else hit this? Curious whether people trust one device more than others and why.
Open Wearables is an open-source platform that turns raw wearable data into something actually useful. One API for multiple wearable providers, open scoring algorithms, and an AI engine that reasons about health data instead of just summarizing it.
Open Wearables
