Research-driven dataset development
Develops audio datasets using a research-style workflow that moves from hypothesis to design, experiment, evaluation, productionization, and release.
David AI builds proprietary audio datasets for speech and conversational AI, helping labs and enterprise teams request samples, license data, and design custom audio datasets.
David AI is an audio data research company that develops proprietary datasets for speech and conversational AI. The site positions audio as the interface it wants to improve, and says the company works with top AI labs and Fortune 100 companies.
Its process is organized around dataset design and validation: identify a capability to unlock, architect the data shape, run targeted collection, evaluate signal quality, scale the dataset, and then publish and continue improving it. The product is therefore best understood as a dataset provider and research partner rather than a software platform.
Develops audio datasets using a research-style workflow that moves from hypothesis to design, experiment, evaluation, productionization, and release.
Publishes and maintains datasets over time rather than treating release as a one-time event.
Provides a flagship English dataset, Converse, built from channel-separated, natural two-speaker conversations across a wide range of topics.
Offers Atlas, a multilingual dataset spanning 15+ languages with dialect and accent metadata in the same format as Converse.
Includes Chorus for three-or-more-speaker conversations, originally designed for speaker-separation and diarization models.
Includes Dialog, a collection of expert conversations across multiple domains, and notes that additional proprietary datasets are available by request.
Teams building speech-to-speech systems can use the dataset catalog to find training data designed around natural conversation and voice interaction.
Localization and multilingual AI teams can work with Atlas, which covers 15+ languages and includes dialect and accent metadata.
Researchers working on diarization or speaker separation can use Chorus, which focuses on conversations with three or more speakers.
Product teams exploring new voice capabilities can request samples, review fit, and then license off-the-shelf datasets for their needs.
Labs that need a different data shape can collaborate with David AI to design a custom dataset for a specific audio AI capability.
David AI describes itself as an audio data research company. It develops proprietary audio datasets for speech and conversational AI rather than a general-purpose software app.
The company says teams start by requesting samples, then enter a data license agreement for the dataset and use cases they need, and receive access to off-the-shelf datasets within one to two days.
The homepage says David AI works with speech recognition, translation, synthesis, and conversational AI teams. Its featured datasets are designed for speech-to-speech, multilingual, and voice interaction systems.
Yes. The homepage says the company frequently partners with research teams to design new shapes of data for specific use cases.
Public pricing details are not shown on the site. The pricing URL in the collected sources returns a 404 Not Found page.