The Agentic Data Company

Companies building speech models today train largely on audiobooks, podcasts, scraped video, and synthetic dialogue. None of these sources reflect how people actually talk in real conversation, which carries identity, emotion, intent, hesitation, and the texture of a room. Models trained without real conversational data exhibit characteristic failures: they miss intent, mishandle turn-taking, and feel uncanny in extended use. Real conversation at the scale and fidelity frontier training requires is not present on the open internet, and it cannot be synthesized without inheriting the limitations of the model that generates it, so it has to be collected directly.

The Agentic Data Company records real people in real conversations and builds audio datasets designed specifically for frontier model training. They work directly with teams training the models that will define voice-based computing, collecting data at the scale frontier labs require and across languages and the long tail of how people actually speak. Every hour of audio is consented, licensed, and paid for at the source. Their offerings include a public dataset (Open Yap 1K) and a range of private datasets covering task-oriented calls, accented English, multilingual conversations, Hinglish ASR, multi-party conversations, and turn-taking evaluations.

Recent progress in speech models suggests that within a decade, most interaction with intelligence will be conducted through speech with human-level fluency, making conversational training data newly critical and currently missing at scale.