Mobile AI Use Case

On-Device AI Observability

Every keyboard prediction, every voice command, every local inference—tracked privately on-device. Finally answer: "How does my phone protect my data while using AI?"

Syntax Decimal SD.32.06

Mobile

Live On-Device Event Stream

LOCAL

Mobile On-Device ML Pipeline

Input

Sensor data

Prep

Preprocess

Local transform

Inference

On-device ML

Lock

Privacy

Data protection

Act

Action

User result

On-Device Query Examples

Keyboard Prediction Audit

Track how keyboard predictions are generated without any data leaving the device.

SELECT prediction_id, input_context,
suggestions, model_version, latency_ms
FROM local_events
WHERE event_id = 'mobile.keyboard.predicted:1'
AND cloud_upload = false

Voice Processing Trail

See how voice commands are processed locally by the assistant.

SELECT utterance_hash, intent_detected,
confidence, processed_locally
FROM local_events
WHERE event_id = 'mobile.assistant.processed:1'
AND on_device = true

Now Playing Detection

Track how ambient music is identified using on-device fingerprinting.

SELECT audio_fingerprint, matched_song,
match_confidence, database_version
FROM local_events
WHERE event_id = 'mobile.nowplaying.identified:1'
AND network_used = false

Privacy Metrics

Verify that sensitive data never leaves the device for ML processing.

SELECT feature_name, data_type,
processed_locally, encrypted_at_rest
FROM local_events
WHERE event_id = 'mobile.privacy.verified:1'
GROUP BY feature_name

Without Event Model

Users can't verify privacy claims

With Event Model

Verifiable on-device processing

Privacy concern

"Is my keyboard data being sent to the cloud?" — no way to verify

AI feature

"How does Smart Reply work?" — black box processing

Data request

"What ML models run on my phone?" — no inventory available

Privacy concern

mobile.keyboard.predicted:1 -> cloud_upload=false, local_only=true

AI feature

mobile.smartreply.generated:1 -> model="on_device_v3", latency=12ms

Data request

mobile.ml.inventory:1 -> models=["keyboard","voice","camera"], all_local=true

Why Observable On-Device AI?

Lock

Privacy Verification

Users can verify that their data never leaves the device for AI processing.

Speed

Latency Transparency

See exactly how fast on-device inference performs compared to cloud.

List

Model Inventory

Complete list of ML models running on-device with their purposes.

Battery

Battery Impact

Track ML inference power consumption for informed user choices.

Shield

Data Minimization

Prove GDPR data minimization through on-device processing logs.

Sync

Model Updates

Track federated learning updates without exposing user data.

Privacy and Regulatory Compliance

GDPR

Data minimization and processing transparency

CCPA

California Consumer Privacy Act compliance

Design

Privacy by Design

Built-in privacy through on-device processing

Store

App Store Privacy

Transparent privacy nutrition labels

E2E

E2E Encryption

Data encrypted at rest and in transit

Fed

Federated Learning

Model improvement without data collection

Make On-Device AI Transparent

Build trust through verifiable privacy with observable on-device ML.

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