Vidaya - Healthspan score from your wearables, labs, and DNA.

@kate_ramakaieva Thank you, Kate! You nailed the core idea, a single timeline is the unlock. Any one reading (a sleep score, one lab value) is just a snapshot, but put wearables, labs, nutrition, DNA, and medical records on the same axis over years and the trends start explaining each other, that's where the "oh, THAT'S why" moments live. Congrats on everything you're building at FuseBase too! Out of curiosity, which of those data types would you connect first?

@raihanshezan hanks, Raihan! Dashboards were the easy 80%, the hard 20% is turning a moving number into "here's what to do on Tuesday." That's the problem we actually wanted to solve, since most of us already had plenty of graphs and no answers. Glad it landed! 🙏

@nir0b Good question. We have a few layers for it: wearable data comes in through a normalization layer that maps every device's output to standardized metrics, so we're comparing like with like. From there, we keep source attribution on every data point, you can always see which device a number came from, rather than silently averaging devices that measure differently (a wrist-based HR and a chest strap genuinely aren't the same measurement). For trends, consistency within a source matters more than absolute agreement between sources, so trend lines respect provenance. And when you ask Vaya about a marker, it cites which sources it drew from, so a device disagreement is visible instead of hidden. The honest answer is that no one should be blending conflicting sensors into one fake-precise number, showing you the provenance is the trustworthy version.

@igorgurovich Igor, this is a fantastic question, and you've described the exact pattern we see too: the person generating the signal and the person acting on it are often different people. Your 82-year-old/daughter example is spot on.

The foundation for this already exists. We built Squads: shared dashboards for small groups, where every member controls exactly which metrics they share, nothing is visible without explicit per-metric consent. It was originally designed for teams (athletes, pilots, military units with a coach or captain view), but a caregiver view is structurally the same thing: a two-person squad where a parent grants their adult child visibility into their Healthspan score and trends.

You're right that the consent surface is why we're deliberate here. The permission model was built consent-first from day one (the sharer opts in per metric, and can revoke), which is what makes extending it to caregiving feasible rather than a rebuild. The pieces we're still careful about are the ones you'd expect: durable consent for someone who may lose capacity to manage settings, and what Vaya should recommend TO the caregiver versus the patient.

Would genuinely love to compare notes given what you're building at Callie Care, the voice-AI + caregiver-dashboard combination is exactly where this converges. I'll take a look at your launch as well! :)