01
Today’s guidance
The Today screen brings sleep, stress, recovery and load into one clear daily view.
See what matters today.
BioVector
Apple Watch recovery coach
Know what
today needs.
BioVector turns Apple Watch signals, sleep, stress, training and routines into clear daily guidance, with your data kept local while your baseline builds.
Download on theApp Store
Available nowOn iOS.
Health optionalAI only with consentNo diagnosis
Decide today and see over time which routines actually help.
For Apple Watch users
Turn signals into today's guidance.
BioVector answers three questions so Apple Watch data becomes useful in the moment and comparable over time.
Today
01What makes sense today?
Clear daily guidance brings sleep, stress, recovery and load into one view.
Context
02Why is it happening?
Coach-style context shows drivers, data quality and uncertainty instead of hard verdicts.
Trends
03What works over time?
Routines, training and sleep patterns become easier to compare across the first nights, weeks and months.
Core features
What matters first.
A local, integrated view of recovery, load and routines.
02
Understand sleep
Sleep details show duration, architecture and possible relationships with your day.
Sleep in context of your baseline.
03
Plan training
The plan helps connect load and recovery in a more useful way.
Manage training load sensibly.
04
Review routines
One active starter routine is free. Pro adds multiple routines and impact review.
Compare effects over time.
How BioVector helps
Open it in the morning.
BioVector shows today's guidance, then helps you review which routines actually seem to help.
01
Today's guidance
BioVector turns sleep, stress and training into a clear daily decision.
02
Routine impact
Start one routine and later review whether it relates to sleep, HRV, resting pulse or stress.
03
Training decisions
Training blocks are reviewed around recovery, load and goals so the next session is easier to choose.
04
Spot patterns
Days, weeks and months show whether recovery, load and routines are moving in a useful direction.
Deeper areas
More context when you need it.
The launch focus stays recovery, training and routines. Lab values, supplements, fasting and cycle context remain available as secondary topics.
Sleep in context
Duration, regularity and sleep architecture are connected with daily response and routines.
Plan training
Load, recovery and plan are reviewed together so the next step is easier to choose.
See what helps
Start one active starter routine for free and review whether sleep, HRV or resting pulse change over time.
Patterns over time
Days, weeks and months make recurring relationships easier to see.
AI guidance
Generated guidance shows drivers, data quality and uncertainty, so you read signals as context rather than diagnosis.
Your data stays yours
The app works locally with the signals you choose to share. You stay in control of Health access, Pro features and privacy.
BioVector Academy
Recovery Academy
Go deeper on sleep, stress, training and routines with cautious educational content and clear notes on data quality.
Enter AcademyFAQ
Clear answers about data, Pro and the App Store.
BioVector is built for Apple Watch users. Without shared Health data, the app remains usable, but daily focus, sleep, stress and training become much more useful with wearable signals. Sparse or missing values are normal during the first week.
Yes. You decide which Apple Health data you share. BioVector explains the purpose during onboarding and can still open without full Health access.
Core features, the Watch app, widgets and one active starter routine stay useful. BioVector Pro unlocks multiple active routines, coach context, weekly and monthly patterns, routine impact and training guidance. Pricing, trial availability and billing terms are shown in the App Store sheet. Cancel anytime through Apple.
No. BioVector is a wellness and self-reflection tool. It does not diagnose, replace medical advice, or promise treatment or cure.
AI context is optional. If you consent and request an analysis, BioVector uses summarized signals to make context, possible drivers and data quality easier to understand.