Your Voice Never Leaves Your Device
Most Whisper apps upload your recordings to cloud servers. We built Whisper Notes to run entirely on-device—no internet, no data collection, no compromise.
Why We Built a Local-First Whisper App
When we started building Whisper Notes, we faced a choice: use cloud infrastructure for transcription (simpler to build, higher accuracy) or run everything on-device (harder to build, complete privacy). We chose on-device processing.
The reason is straightforward. Voice recordings contain biometric data that cannot be changed after exposure. Unlike a password, you cannot reset your voice. Once uploaded to a cloud service, your audio exists on infrastructure you do not control—subject to breaches, training data pipelines, and retention policies you may never see.
Whisper Notes uses OpenAI's Whisper Large V3 Turbo model running natively on Apple Silicon. Your audio is processed by your device's Neural Engine. No internet connection required. No data transmitted. The app literally cannot phone home because it has no server to call.
The Hidden Cost of "Free" Whisper Apps
In our experience, "free" transcription tools follow a consistent pattern: they upload your audio to cloud servers, process it remotely, and retain data to improve their models. The product is not the software—it is your voice.
Voice Data Is Permanent
Unlike passwords or credit card numbers, voice biometrics cannot be changed after compromise. A few seconds of recording captures acoustic signatures that identify you across different contexts.
Voice cloning technology now requires only three to five seconds of sample audio. Human detection accuracy for high-quality voice deepfakes remains at just 24.5%. In 2025, a voice clone of the Italian Defense Minister was used to extract nearly one million euros. This is not a theoretical risk.
When you upload audio to a cloud transcription service, you are creating a permanent record of your biometric identity on infrastructure you do not control.
The Cloud Transcription Breach Landscape
AI-related security incidents increased 56.4% in 2024. Eighty-two percent of breaches now involve cloud infrastructure. Healthcare has seen protected health information exposure via transcription agents, EHR integrations, and misconfigured data lakes.
The pattern is predictable: sensitive data flows into AI systems, visibility drops, and attackers or accidents expose what was meant to be private. Contact center transcripts stream to models while account numbers land in debug logs without masking.
The first half of 2025 saw a sharp rise in major data breaches involving more sensitive categories of data. Instead of just usernames and passwords, breaches now expose genetic profiles, voice recordings, and biometric identifiers.
The Direction of Travel
In March 2025, Amazon announced it was discontinuing the "Do Not Send Voice Recordings" setting on Echo devices. All user interactions with Alexa devices are now recorded and sent to Amazon's servers by default, with no option to opt out.
This is not an isolated decision. Major platforms are moving toward more data collection, not less. The economic incentives of AI development favor accumulating training data. Privacy options that exist today may not exist tomorrow.
We built Whisper Notes with the opposite architecture: there is no server to send data to. This is not a setting that can be changed. It is a fundamental constraint of how the app is built.
The True Price of "Free"
Free Whisper web tools often use your audio to improve their models. This is disclosed in terms of service that few users read. Per-minute cloud services at $0.006 to $0.40 per minute accumulate to hundreds of dollars annually for regular users.
Subscription-based services like Otter.ai cost approximately $99 per year. Over five years, that is $495—for a service that processes your audio on remote servers.
Whisper Notes costs $4.99 once. No subscription. No per-minute fees. No data collection. The business model is simple: you pay for software, you own the software.
Total Cost of Ownership
| Service Type | Year 1 | Year 3 | Year 5 | Data Handling |
|---|---|---|---|---|
| Whisper Notes | $4.99 | $4.99 | $4.99 | Never leaves device |
| Subscription Service | $99 | $297 | $495 | Cloud processed |
| Per-Minute Cloud API | $120-480 | $360-1,440 | $600-2,400 | Cloud processed |
| "Free" Web Tools | $0 | $0 | $0 | Used for AI training |
When Cloud Services Make Sense
The trade-off is real. Cloud services can offer slightly higher accuracy (95-98% versus our 92%) because they run larger models that will not fit on consumer devices. They can also offer real-time transcription with lower latency than on-device processing.
If you need the absolute highest accuracy, do not handle sensitive data, and have reliable internet connectivity, cloud services may be appropriate for your use case.
But for most professional applications—healthcare documentation, legal proceedings, journalism interviews, confidential business communications—the privacy trade-off is not worth the marginal accuracy gain. A 3% accuracy improvement does not justify uploading sensitive recordings to infrastructure you do not control.
Why Architecture Matters: Native Apps vs. Web Wrappers
When you search "Whisper app," you will find three categories: web-based tools running in your browser, cloud APIs that require internet, and native apps compiled specifically for your device. The architecture difference matters for both privacy and performance.
Web Wrappers and Browser-Based Tools
Many browser-based Whisper tools claim "local processing," which is technically accurate. Your audio stays in the browser tab. But browser environments have fundamental limitations.
Memory constraints force smaller models. Most browsers limit WebAssembly memory to around 4GB, which restricts the model size that can run. JavaScript adds processing overhead compared to native code. A single tab crash loses your work with no recovery option.
Browser-based tools also lack system integration. They cannot run in the background while you use other applications. They cannot access hardware acceleration efficiently. They are web pages that happen to do transcription, not transcription software.
| Processing | WebAssembly/TensorFlow.js in browser |
| Model Size | Limited by browser memory (~4GB) |
| Speed | Slower due to JavaScript overhead |
| Privacy | Better than cloud, but browser has access |
| Reliability | Tab can crash, no background processing |
Native Apps: Direct Hardware Access
Whisper Notes is compiled specifically for macOS and iOS. It accesses Apple's Neural Engine directly—the same dedicated chip that powers Face ID and computational photography.
This is not a web page wrapped in an app shell. It is native code optimized for your specific hardware. The Whisper Large V3 Turbo model runs at full capacity, processing audio up to ten times faster than real-time on Apple Silicon Macs.
Native apps can run in the background, integrate with system services, and recover gracefully from interruptions. They are sandboxed by the operating system, meaning they cannot access data from other apps. And because Whisper Notes requests no network permissions, it literally cannot transmit data even if compromised.
| Processing | Direct Apple Neural Engine access |
| Model Size | Full Whisper Large V3 Turbo (1.2GB) |
| Speed | Up to 10x real-time on Apple Silicon |
| Privacy | Sandboxed, no network permissions |
| Reliability | Background processing, system integration |
Cloud APIs: Maximum Power, Maximum Exposure
Cloud services can run the largest Whisper models because server resources are effectively unlimited. They can offer marginally higher accuracy and features like real-time transcription that require substantial compute power.
The trade-off: every recording uploads to infrastructure you do not control. Your audio traverses the internet, is processed on remote servers, and may be stored according to retention policies you did not choose.
For therapists bound by confidentiality requirements, lawyers handling privileged communications, journalists protecting sources, or anyone working with sensitive information, cloud processing is often a disqualifying factor regardless of accuracy benefits.
| Processing | Remote servers (unlimited compute) |
| Model Size | Largest available models |
| Speed | Depends on internet and server queue |
| Privacy | Audio uploaded and potentially stored |
| Reliability | Requires internet, subject to rate limits |
Our Architectural Decision
We chose native app architecture because it is the only way to guarantee your voice data stays on your device. Not "processed locally then synced." Not "encrypted in transit." Never uploaded, period.
This choice has costs. We cannot offer real-time transcription during recording. We cannot run models larger than what fits on your device. We cannot provide collaborative features that require a server.
We made this trade-off intentionally. For the use cases where privacy matters—and in our experience, that includes most professional transcription—the guarantee of local processing outweighs the features that require cloud infrastructure.
Technical Foundation: Whisper Large V3 Turbo
The AI Model
Specifications
| AI Model | OpenAI Whisper Large V3 Turbo |
| Languages | 99 languages with technical vocabulary |
| Audio Formats | MP3, WAV, M4A, FLAC, AAC, OGG, WMA |
| Processing Speed | Up to 10x real-time on Apple Silicon |
| File Size Limit | None (limited by device memory) |
| Platforms | iOS 18+ (iPhone 12+), macOS 11+ (Apple Silicon) |
Core Features
Whisper Notes is designed for professional transcription workflows where privacy and reliability matter.
File Import and Batch Processing
Import audio files from any source for offline transcription. The app processes complete files rather than streaming, which allows the model to use full context for improved accuracy.
- ✓Import from Files, Voice Memos, or any app that shares audio
- ✓Process multiple files in sequence
- ✓Background processing while using other applications
- ✓Automatic organization by date and source
Export Formats
Multiple output formats for different professional workflows.
- ✓Plain text with paragraph formatting
- ✓SRT and VTT subtitle files for video
- ✓Timestamped transcripts for reference
- ✓Speaker labels for multi-person recordings
- ✓Custom paragraph break settings
Privacy Architecture
The app is built so that your audio cannot leave your device, not as a setting but as a technical constraint.
- ✓No network permissions requested or granted
- ✓No cloud servers to connect to
- ✓No analytics or telemetry collection
- ✓Local storage only, encrypted by iOS/macOS
- ✓HIPAA and GDPR compliant by architecture
Accuracy Analysis
Testing methodology and results
We tested Whisper Notes accuracy across 500 audio samples covering studio recordings, phone calls, meetings, medical terminology, legal proceedings, and various accents. Results were verified by professional transcriptionists.
Accuracy by Audio Type
| Audio Type | Sample Size | Accuracy | Notes |
|---|---|---|---|
| Studio Quality Speech | 100 samples | 92.4% | Clear audio, single speaker |
| Phone Call Quality | 75 samples | 83.7% | Compressed audio, typical phone quality |
| Meeting Recordings | 100 samples | 87.2% | Multiple speakers, room acoustics |
| Medical Terminology | 50 samples | 89.1% | Technical vocabulary recognition |
| Legal Proceedings | 75 samples | 88.5% | Formal speech, legal terminology |
| Accented English | 100 samples | 81.4% | Performance varies by accent |
Key Findings
- •Accuracy is 15-25% higher than built-in device transcription
- •Medical and legal terminology achieves 88-89% accuracy
- •Performance decreases proportionally with audio quality
- •Multi-speaker scenarios maintain 85-87% accuracy
Cloud services using larger models achieve 95-98% accuracy on clean audio. The 3-6% accuracy gap is the trade-off for complete privacy. For most professional use cases, 88-92% accuracy with privacy is preferable to 95-98% accuracy without it.
Market Comparison
How Whisper Notes compares to alternatives
A direct comparison of Whisper Notes against cloud transcription services, built-in device tools, and enterprise software.
Feature Comparison
| Feature | Whisper Notes | Cloud Services | Built-in Tools | Enterprise Software |
|---|---|---|---|---|
| Accuracy (clean audio) | 92.4% | 95-98% | 75-85% | 90-95% |
| Privacy | Complete (on-device) | Data uploaded | Varies by vendor | On-premise option |
| Cost | $4.99 once | $0.006-0.40/min | Free (limited) | $500-2000/license |
| Languages | 99 languages | 50-100 languages | 10-30 languages | 20-50 languages |
| Internet Required | No | Yes | Sometimes | Depends on deployment |
| File Length Limit | Device memory only | 1-2 hours typically | 5-10 minutes | Varies |
Market Position: Whisper Notes occupies a specific position: professional-grade accuracy with complete privacy at consumer pricing. Cloud services offer higher accuracy without privacy. Enterprise software offers privacy at enterprise pricing. We offer the middle ground that most professionals actually need.
Professional Use Cases
Where local-first transcription matters
Healthcare
Medical professionals use Whisper Notes for patient documentation, clinical notes, and research interviews. The on-device architecture satisfies HIPAA requirements without requiring enterprise infrastructure.
Use Cases
- •Patient consultation documentation
- •Medical procedure notes
- •Research interview transcription
- •Telemedicine session records
- •Clinical training content
Benefits
- ✓HIPAA compliant by architecture, not by policy
- ✓Medical terminology achieves 89% accuracy
- ✓No PHI exposure to cloud services
- ✓Reduces documentation time significantly
Legal
Attorneys and legal professionals use Whisper Notes for depositions, client interviews, and case preparation. Attorney-client privilege is protected because recordings never leave the device.
Use Cases
- •Client interview documentation
- •Deposition transcription
- •Case research notes
- •Legal proceeding records
- •Investigative interviews
Benefits
- ✓Attorney-client privilege protected by architecture
- ✓Legal terminology achieves 88.5% accuracy
- ✓Court-ready transcript formatting
- ✓Fraction of professional transcription cost
Journalism
Journalists use Whisper Notes for source interviews and field recordings. Source protection is guaranteed because recordings cannot be subpoenaed from servers that do not exist.
Use Cases
- •Source interview transcription
- •Field recording documentation
- •Press conference notes
- •Research interview archives
- •Podcast production
Benefits
- ✓Source protection through architecture
- ✓Works offline in any location
- ✓No third-party access possible
- ✓Professional workflow integration
Performance and Limitations
What to expect from on-device processing
Performance Benchmarks
Processing speed depends on your device hardware. Newer Apple Silicon provides faster transcription.
Processing Speed
iPhone 15 Pro: 1 hour audio processes in approximately 6-8 minutes
Up to 10x faster than real-time on Apple Silicon
Battery Usage
1 hour of audio transcription uses approximately 8-12% battery
Optimized for Apple Neural Engine efficiency
Storage Requirements
App size: 1.2GB (includes Whisper model). Transcripts: approximately 0.1MB per hour of audio
Compressed text output minimizes storage
Memory Usage
Peak RAM usage: 2-3GB during active processing
Requires 4GB RAM minimum (iPhone 12 or later)
Known Limitations
On-device processing involves trade-offs. We believe these are acceptable for most professional use cases, but you should understand them before purchasing.
Device Requirements
Requires iPhone 12 or later, or Apple Silicon Mac. Older devices lack the Neural Engine performance for practical use.
Impact: Not compatible with devices more than 4-5 years old
Processing Time
Long recordings require proportionally longer processing time. There is no way around the physics of on-device computation.
Impact: A 4-hour recording takes 30-40 minutes to process
Audio Quality Dependency
Poor audio quality or loud background noise reduces accuracy. The model cannot recover information that is not in the signal.
Impact: Accuracy may drop to 70-80% with poor recordings
No Real-Time Transcription
The app transcribes after recording completes, not during. This is an intentional choice: full-file processing produces more accurate results.
Impact: Not suitable for live captioning use cases
Single Language Per Recording
Rapid language switching within a single recording reduces accuracy. The model performs best with consistent language throughout.
Impact: Best results with one primary language per file
Summary
Download Whisper Notes
Local-first transcription for iPhone and Mac. Your voice, your device, your data.
Download on App StoreAvailable on iOS (iPhone 12+) and macOS (Apple Silicon). $4.99 one-time purchase. No subscriptions. No in-app purchases.