About KreyAI

KreyAI is a language technology company building practical tools for Haitian Creole and multilingual work. The first product is transcription for audio, subtitles, and speaker-labeled transcripts. Adwaz is the private-beta writing assistant for Haitian Creole.

Most services struggle when language moves outside a narrow mainstream pattern. We build KreyAI products to preserve meaning, structure, and cultural context for journalists, legal professionals, researchers, educators, creators, interpreters, translators, and community organizations.

Product Family

• KreyAI transcription for audio, subtitles, speaker labels, and transcript exports
• Adwaz private beta for Haitian Creole writing review, spelling, grammar, and orthography
• A shared privacy posture: process the work, avoid unnecessary retention, and never use customer content for model training

Our Approach

KreyAI focuses on producing language output that is not only accurate, but usable.

• clear paragraph structure
• optional speaker labeling
• support for multilingual and mixed-language audio
• export formats suited for subtitles and production workflows

The goal is simple: output that feels considered, not raw.

Privacy by Design

Your data is a guest, not a product. We take a minimal and respectful approach to user data because sensitive audio deserves careful handling by default.

• Files are stored in active storage for up to 7 days to allow re-download, then scheduled for automatic deletion.
• Audio and transcripts are never used to train AI models.
• The email-based workflow avoids traditional account creation and reduces unnecessary personal data collection.

KreyAI is built to process your data, not retain it.

Why KreyAI Exists

Language is nuanced. Transcription tools often overlook that nuance, especially when multiple languages are involved.

KreyAI is an attempt to move closer to how language is actually used, with a focus on clarity, structure, and real-world application.

Built With Intention

KreyAI is developed with input from real-world language experience across translation, interpretation, and multilingual communication.

It is still evolving, and feedback plays an important role in shaping what comes next.