Israeli startup aiOla has released Whisper-NER, an open-source AI model that transcribes audio while automatically masking sensitive information. As reported by Carl Franzen for VentureBeat, the model builds upon OpenAI’s Whisper framework and combines automatic speech recognition with named entity recognition to protect private data during transcription. The tool can identify and obscure sensitive details like names, phone numbers, and addresses in real-time, making it particularly valuable for industries handling confidential information. Available on Hugging Face and GitHub under the MIT License, Whisper-NER allows organizations to freely modify and deploy it for commercial use. According to aiOla’s Vice President of Research Gill Hetz, the model was specifically designed to advance privacy in AI while maintaining transcription accuracy.