NapBot Integration

Stream NapBot data. Straight from the phone.

NapBot tracks sleep automatically and classifies its stages on-device with CoreML, writing the session — light, deep, REM, and awake — to Apple Health, and Sahha’s SDK reads it into your app as normalized sleep biomarkers, alongside every other source.

On-device
Apple Health
iOS
HIPAA
GDPR

Start building Read the SDK docs

Free for 30 days · No credit card

Normalized Auto-synced

Sleep duration: 7:26 h
Deep sleep: 84 min
REM sleep: 96 min

Identical schema across 500+ sources

How it works

Your users connect NapBot. Sahha does the rest.

This is your user’s side of the story — one screen, once. Sahha ingests every NapBot signal, normalizes, deduplicates, and delivers it to your service — raw, or as refined intelligence your product can act on.

Allow "your app"

Sleep

Activity

Heart rate

Connect

9:41LIVE

82READY

Sleep7h 12m

Steps5,993

Heart rate62 bpm

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20% off açaí bowls — today only.

Sahha

Permissions handled

Encrypted in transit

History backfilled

Background sync enabled

Cleaning · deduping · scoring

Raw data logs Biomarkers Scores Insights Archetypes Tags

Real-time webhooks

Always in sync

Query via API

Access controlled

Your service

Waiting for data…

On-device and permissioned

NapBot data is read on the user’s own device, only after they grant Apple Health permission — nothing syncs without consent.

One integration, every source

Permission is per data type, not per brand. Anything that writes to Apple Health — NapBot today, a new watch next year — flows through the same SDK with no extra prompt and no new code.

Data coverage

What NapBot syncs through Apple Health.

Request only what you need
You choose exactly which of these signals to request from Apple Health — users are only ever prompted for those, which keeps opt-in rates high.
One schema, every source
NapBot, Apple Watch, and Oura all return the same fields and units.
What crosses the bridge
The sleep session and its light, deep, REM and awake stages pass through Apple Health; some app-exclusive metrics may not.

Sleep

HealthKitSahha

sleepAnalysis · asleepsleep_durationmin
sleepAnalysis · asleepCoresleep_stage_lightmin
sleepAnalysis · asleepDeepsleep_stage_deepmin
sleepAnalysis · asleepREMsleep_stage_remmin
sleepAnalysis · awakesleep_stage_awakemin

See a real payload

HealthKit · sleep

{
  "type": "HKCategoryTypeIdentifierSleepAnalysis",
  "value": "HKCategoryValueSleepAnalysisAsleepDeep",
  "startDate": "2026-06-03T01:12:00Z",
  "endDate": "2026-06-03T02:36:00Z",
  "sourceRevision": { "source": { "name": "NapBot" } }
  // …light, REM & awake segments across the session
}

Sahha · normalized

[
  {
    "category": "sleep",
    "type": "sleep_stage_deep",
    "value": 84,
    "unit": "minute",
    "periodicity": "daily",
    "aggregation": "total",
    "startDateTime": "2026-06-02T23:20:00Z",
    "endDateTime": "2026-06-03T06:46:00Z"
  },
  {
    "category": "sleep",
    "type": "sleep_stage_rem",
    "value": 96,
    "unit": "minute",
    "periodicity": "daily",
    "aggregation": "total",
    "startDateTime": "2026-06-02T23:20:00Z",
    "endDateTime": "2026-06-03T06:46:00Z"
  }
  // …3 more normalized logs
]

NapBot classifies sleep stages on-device with CoreML, and the session plus its stages is all that crosses. NapBot also surfaces sleep-apnea analysis and environmental sound exposure — neither reaches Sahha, because Sahha has no biomarker for apnea events and none for noise or sound exposure. NapBot is Apple-Watch-based, so a user without a watch produces nothing at all. It’s a consumer sleep app, so accuracy varies with how the user tracks; where they also wear another device writing sleep to Apple Health, Sahha deduplicates the overlapping sessions.

Missing a metric you need? Talk to us in the Sahha Slack — if NapBot captures it, we can usually add support.

Get more than just raw data

Sahha turns these signals into biomarkers, scores, archetypes, and insights — the modeling done for you.

Biomarkers

Scores

Archetypes

Insights

Reading Apple Health yourself? Here’s the to-do list.

Everything on the left is yours to write, test, and maintain on iOS. Everything on the right, Sahha already did.

Build it yourself

With Sahha

Every device

Build it yourself

Integrate Apple Health.
Handle iOS version differences.
Add Health Connect separately for Android.

With Sahha

One SDK covers Apple Health, Health Connect, and every cloud source.

Getting the data

Build it yourself

Write the HealthKit queries.
Request the right permissions.
Wire up background delivery.

With Sahha

The SDK handles queries, permissions, and background sync.

Keeping it clean

Build it yourself

Dedupe apps writing the same metric.
Map dozens of HealthKit types.
Reconcile against your Android sources.

With Sahha

Deduped, typed, one schema — one stream per user.

Turning it into insight

Build it yourself

Build a sleep model.
Build an activity model.
Hire a data scientist.

With Sahha

Scores, archetypes, and insights — built in.

Keeping it alive

Build it yourself

Apple changes a HealthKit API.
You find out in production.

With Sahha

We version the SDK. You never notice.

No NapBot developer account needed — Sahha reads what NapBot already writes to Apple Health on iOS.

Setup

Live in an afternoon, not a sprint.

# Add the Sahha SDKnpm install sahha-react-native
01
Add the Sahha SDK
Drop the Sahha SDK into your iOS app — or React Native or Flutter. The same SDK also covers Health Connect for your Android sources.
A
Allow “your app”
Sleep
Activity
Heart rate
Connect
02
Prompt for Apple Health permissions
Call the SDK to show the native Apple Health consent sheet. The user chooses what to share — under your brand. It’s one prompt, ever: permission is per data type, not per brand, so every future source is already covered.
Your app LIVE
Sleep7h 12m
Readiness82
Heart rate62 bpm
03
Sahha reads and delivers
Once permission is granted, the SDK reads NapBot data from Apple Health in the background, normalizes it to one schema, and streams it to your app by webhook or API.

Start building Read the SDK docs

Most teams read live NapBot data the same day they add the SDK. The only per-source prerequisite: your user has NapBot’s Apple Health sync switched on — most source apps enable it by default.

Destinations

Route it into your stack.

Sahha streams every update to your webhook — and a step-by-step guide takes it the rest of the way into your database, CDP, or messaging tool.

FAQ

NapBot integration questions

How does Sahha get NapBot data?

NapBot writes each automatically tracked sleep session to Apple Health, and Sahha reads it from there with its mobile SDK, delivering it as normalized sleep biomarkers — no NapBot API to integrate.

Does the user have to start and stop tracking?

No. NapBot detects sleep automatically and classifies the stages on-device with CoreML, so nights land in Apple Health without the user tapping anything. That makes it a steadier source than trackers that depend on someone remembering to hit a button.

What NapBot data does Sahha receive?

The sleep session and its stages — light, deep, REM, and awake. NapBot’s sleep-apnea analysis and its environmental sound exposure do not cross: Sahha has no biomarker for apnea events and none for noise or sound exposure, so those stay in NapBot. Accuracy varies with how the user tracks, and where another device also writes sleep to Apple Health, Sahha deduplicates the overlapping sessions.

Does the NapBot integration work on Android?

No. NapBot is an iOS app that writes to Apple Health, so this is an iOS-only integration — and because tracking is Apple-Watch-based, a user without a watch produces no NapBot data at all. Your users’ other Android sources still flow through the same Sahha SDK.

Is the NapBot integration HIPAA and GDPR compliant?

Yes. Sahha is HIPAA and GDPR compliant and SOC 2 certified, and NapBot data flows through the same compliant pipeline as every other source.