Every wearable, one API.
Built for coaches and AI agents.

Garmin, Oura, Whoop, Apple Health and ten more sources, normalized into one feed. Read it yourself, or let your AI coach do it.

Connect your first athlete → Works with Claude MCP
Ridgeline Coaching Overview Athletes Sources Webhooks API keys Settings

Maya Lindqvist

Ultra · 100 mi build · week 9
Readiness
72/100
HRV · RMSSD61ms↓ 14% vs 7-day
Sleep7:32h↑ 38 min
Resting HR48bpm± 0
HRV · last 14 nightsGarmin + Oura
Connected sources
Garmin2 min ago
Oura06:12
Stravayesterday
Apple Healthinvite sent
Last workout
Long run · 32.4 km+1,240 m · Z2 71% · 3:18:40

Platform

One platform.
Every source of signal.

Cloud wearables, phone health stores, webhooks and an MCP server in one platform.

Cloud wearables

Garmin, Oura, Whoop, Polar, Suunto, Strava and more over OAuth.

OURA GARMIN WHOOP POLAR
10 cloud providersHistorical backfill on connect

Phone health SDKs

Apple Health, Samsung Health and Health Connect from your own app.

SwiftHealthKitKotlinHealth ConnectFlutteriOS + AndroidReact NativeiOS + Android
Background syncFull Apple Health XML import

One data model

Same names and units, whatever the device on the wrist.

{ "source": "garmin", "hrv_rmssd_ms": 61, "resting_hr_bpm": 48, "sleep_minutes": 452, "deep_minutes": 88 }
Source priority rulesDuplicates merged

Webhooks

Know the moment a night or a session lands.

sleep.created200
workout.created200
recovery.updated200
connection.added200
Signed payloadsDelivery log and retries

AI and MCP

Agents query sleep, recovery and workouts in plain language.

How did Maya sleep this week?→ get_sleep_summaries6 h 58 min average, deep sleep down 12% after Tuesday's long run.
Claude, Cursor, your agentsBuilt-in MCP server

Coach portal

Invite athletes, watch syncs and manage keys in one place.

garmin · synced 2 min ago
oura · synced 06:12
strava · synced yesterday
Team invitesSync history per athlete

Connects to

GarminOuraWhoopPolarSuuntoStravaFitbitWithingsUltrahumanGoogle HealthApple HealthSDKSamsung HealthSDKHealth ConnectSDK

Use cases

Built for your sport

From ultra runners to group classes, coaches see the same clean numbers whatever their athletes wear.

1Endurance and trail running

Endurance and
trail running

Long runs, vert and heart-rate zones come back from Garmin, Suunto, Polar and Coros via Strava. No manual logging.

2Clubs and group training

Clubs and
group training

Members bring whatever they own. Show steps, active minutes and class workouts without picking a hardware partner.

3Cycling and triathlon

Cycling and
triathlon

Ride, swim and run sessions in one timeline, with training load and recovery side by side.

4Recovery and longevity

Recovery and
longevity

Sleep stages, HRV and skin temperature trends next to lab results and body scans in your own platform.

How data moves

One link in.
One feed out.

Send the athlete a link. They pick their device and sign in once. Everything after that is automatic.

Garmin watch OAuth
Oura ring OAuth
Whoop strap OAuth
iPhone · Apple Health SDK
AnyWatch

Normalize, merge, deliver

  1. Backfill past months on first connect
  2. Normalize names, units and time zones
  3. Merge overlapping devices by your priority rules
  4. Deliver over REST, webhooks and MCP
Coach dashboard REST
Member app Webhook
AI coach MCP
Your warehouse Export

Training data is everywhere.
AnyWatch turns it into one feed.

Data

The numbers
coaches actually use.

Daily summaries, time series and events in the same units across every source.

Sleep

Duration · stages · efficiency · naps

Deep 1:28REM 1:44Light 3:56Awake 0:24

HRV

RMSSD · ms · overnight

Resting heart rate

bpm · daily

48bpm

Workouts

Distance · pace · elevation · zones

Activity

Steps · active kcal · vigorous minutes

11,482steps

Recovery and body

SpO₂ % · skin temp deviation °C · weight kg · body fat % · cycle day

SpO₂
97%
Skin temp
+0.3°C
Weight
58.4kg

AI-native

Let your AI coach read the watch.

Who slept badly this week and still has a hard session tomorrow? → get_sleep_summaries · get_timeseries(resting_hr) · training plan Two athletes. Maya averaged 5 h 50 min with HRV down 18% before 6 × 800 m. Jonah's resting HR is up 7 bpm ahead of a 30 km long run. Consider easy aerobic days for both.

MCP server included. Connect Claude, Cursor or your own agents in minutes.

Live heart rate152 bpm · Z3

Security and control

Health data, handled with care

Athletes choose what to connect. You decide how long data stays and who can read it.

Athlete consent

Athletes connect each device themselves and can disconnect at any time. Nothing syncs until they sign in with their own account.

Signed webhooks

Every delivery is signed and logged, with retries and test events.

Delete on request

Remove a user and their data, including queued webhook payloads, in one call.

Retention you set

Archive raw data after a period you choose, or keep it forever.

Source priorities

Decide which device wins when a watch and a ring both report the same night.

Stop integrating watches.
Start coaching with the data.

Get started → Read the API →