How Besimple AI is Building the Data Layer for AI, Starting with Audio

Besimple AI, building the data layer for AI, led by Yi Zhong and Bill Wang, has secured $3M in a seed round from Y Combinator, Surgepoint Capital, Porterfield Ventures, Amino Capital, WELIGHT Capital, Multimodal Ventures, Script Capital, and several amazing angel investors.

The concept originated from challenges encountered at Meta, where training advanced AI models demanded vast amounts of high-quality data, an increasingly difficult resource to obtain. After years of building large-scale data systems for the Llama team, the founders are now applying that operational expertise to the audio domain. Audio represents the most natural interface for generative AI, and significantly larger datasets will be required to power the next generation of conversational models.

The process begins with large-scale data collection, assembling a proprietary dataset of diverse conversational audio spanning multiple languages, dialects, and accents. Human expert annotators, supported by an in-house annotation platform, then process this audio for Automatic Speech Recognition, delivering human-level transcription and diarization. This high-fidelity data advances the frontier of audio model performance. The dataset now includes millions of hours of conversational audio and continues to grow rapidly.