Ghost Pepper Meet local meeting transcription and diarization
Local Whisper + Qwen cleanup beats cloud transcription when privacy matters.

Custom PII model runs on-device before AI sees anything—solves real data exposure in meeting tools.
Legal firms, medical practices, executives handling sensitive conversations, enterprise compliance teams
Otter.ai · Fireflies.ai · Grain
Every AI meeting tool sends conversations to the cloud. I trained my own PII model - 72M words, 100% catch rate on real meetings. Before anything touches AI, names become aliases, amounts scramble, identifiers vanish.
Everything runs on-device. Nothing leaves your machine.
Free for now - can't afford Apple's $99 notarization yet. Happy to answer questions about the tech.
Local Whisper + Qwen cleanup beats cloud transcription when privacy matters.
Local MLX model redacts PII without sending documents to the cloud.
Fully local transcription with auto meeting detection beats cloud services on privacy.
Stops zero-width Unicode bypasses that break standard PII filters before LLM calls.
Native Swift implementation beats Electron wrappers with sub-300ms latency on Apple Silicon.
Offline redaction with custom threat feeds—but pattern matching has blind spots.