Silent-Night is a medical-category app for iOS that uses on-device machine learning to detect snoring and trigger vibration-based position changes.
Product velocity
Unknown
Daily rank 🇺🇸
—
Medical
Sentiment
1.0
3 reviews
Nemesis
SnoreLab : Record Your Snoring
The App DNA
What makes this app unique?
Users hire the app to reduce partner sleep disturbance without relying on medical devices or cloud-based data storage.
For Individuals who snore and their partners seeking a non-medical, natural method to reduce sleep disturbance.
What does it look like?
Key features
App detects snoring sounds and triggers device vibrations to prompt a change in sleeping position
All audio evaluation and machine learning processes occur locally on the device with no cloud transmission
How much does it cost?
The app is currently offered as a free utility with no visible subscription or IAP gates.
Velocity
Steady developmentShow more...
Who built it?
Mobile Box - App Consulting UG (haftungsbeschraenkt)
1 app tracked · Medical
Explore the full publisher profileUser Sentiment
What do users think recently?
Review voice lately leans frustrated.
How are ratings & reviews evolving?
Not enough recent reviews to extract reliable themes yet.
Read the full review analysisCompetition
Competitive landscape for Silent-Night - Anti Snoring
How's the Medical market?
The app occupies a niche medical-utility space with a 1-star rating across 3 ratings. The lack of review volume relative to established competitors signals low market penetration.
Read the market outlookThe rivals identified
By Reviva Softworks Ltd
Dominates the anti-snoring niche with a massive, long-standing user base and specialized focus on sleep sound analysis.
- Provides clinical-grade sleep sound analysis and snoring intensity tracking that goes beyond simple noise detection.
- Maintains a specialized focus on long-term snoring trends, allowing users to correlate lifestyle changes with snoring reduction.
- Offers a sophisticated data visualization suite that helps users identify specific triggers for their snoring patterns.
Unlock the head-to-head verdict: where this rival wins, and where it loses.
Access the full report for freeThe Analyst's Read
Key takeaways for Silent-Night - Anti Snoring
Where is it heading?
Users report: The anti-snoring market is consolidating around apps that provide actionable, long-term health data. Silent-Night remains exposed due to its focus on immediate, unverified intervention, so the PM must shift toward data-driven insights to remain relevant.
- The 1-star rating baseline indicates the core detection algorithm is failing to satisfy users, which will accelerate churn into the next quarter.
- Lack of longitudinal data tracking prevents the app from competing with SnoreLab, limiting its ability to capture the power-user segment.
The SWOT
- On-device processing [Privacy-first architecture]
- Offline-first operation [Data security moat]
- Wearable integration [Market parity]
- Clinical data export [User retention]
Next best moves
Audit detection algorithm because 1-star rating indicates failure to trigger correctly → recover rating baseline
+ 1 more prioritized moveThe counter-intuitive read
The privacy-first, offline-only architecture is a liability in…
Read the full takeFeature gaps
Longitudinal snoring trend tracking (available in SnoreLab but missing here) +1
Since the last report: The app has adopted a privacy-first, on-device machine learning identity, but the transition is currently undermined by a 1-star rating and lack of longitudinal tracking features.
Bottom line
The app offers a unique privacy-first approach, but the 1-star rating indicates the core detection mechanism is failing, so the PM must prioritize algorithm reliability over new features to prevent total churn.
Unlock 3 critical frictions, 2 market threats, 1 more prioritized move and the analyst’s take.
Access the full report for freeReport last updated