Voice check-ins
Check in without admin
PocketCoach supports morning check-ins and workout feedback by voice, with on-device transcription and stored text context.
PocketCoach supports morning check-ins and session feedback by text or voice. Raw audio is intended to be transcribed on device and discarded, while the transcription text can be stored as coaching context.
Say what changed
Sleep was poor. The knee is tight. Work moved the session. Voice check-ins let the user capture useful context quickly, then inspect the text that remains.
"Slept badly. Legs are heavy. Keep today easy."
Check-in details
Morning readiness, energy, soreness, weight, and notes.
Optional session feedback after manual completion.
Typed fallback for accessibility and accuracy.
On-device transcription intent for raw audio minimisation.
Stored text can support future coaching conversations.
Say it once, on the move.
A quick voice note about sleep, soreness, or how the session felt is transcribed on device, then stored as text your coach can use. No typing at a desk, no lost context between sessions.
Clear answers
Is raw audio stored?
Current app docs say raw audio is intended to be transcribed on device and discarded. Only transcription text is stored.
Can I type instead?
Yes. Typed input is available as a fallback.
Why does check-in data matter?
It gives the AI coach context such as sleep, soreness, energy, schedule pressure, and session feedback.
Check in by voice
Join the waitlist for voice check-ins that give your AI coach real context.