Announcing Our $25M Series A

We founded David AI less than a year ago to build the data layer for audio AI. Today, we’re a trusted partner to many of the world’s leading AI labs, and our data supports cutting-edge voice production systems and frontier research.

We’re excited to announce our $25 million Series A, led by Alt Capital and Amplify Partners, with participation from First Round Capital, Y Combinator, BoxGroup, and other great investors. We’re thrilled to welcome a group of angel investors who collectively bring decades of experience in frontier audio research, and to welcome Jack Altman to our board.

Our Mission

At David AI, our mission is to bring AI into the real world—and we believe voice is how that will happen.

Today, we’re seeing AI phone agents take hold (e.g., in customer support), but the scope of voice AI’s impact will be much larger.

Many of the most promising real-world AI use cases rely on audio as an interface. Think humanoid robots, wearable devices, and everyday tools and assistants embedded into your daily life. All of these depend on voice to meaningfully interact with.

The Audio Data Problem

As audio AI advances and new use cases emerge, high-quality training data is the bottleneck.

Voice AI apps are only as good as the models they rely on—and those models are only as good as the data they’re trained on.

For example, many labs are investing in end-to-end speech model architectures. A 2024 paper from Meta AI emphasized the need for millions of hours of full-duplex, channel-separated speech to feed’ these models. Yet across all publicly accessible datasets, only a few thousand hours exist in the right format:

“Compared to text-based chat datasets, spoken dialogue data is limited. A combination of all significant spoken dialogue datasets… would still result in only ∼3k hours.”
– “Beyond Turn-Based Interfaces: Synchronous LLMs as Full-Duplex Dialogue Agents,” Meta AI, 2024

This is where David AI comes in.

Building a Data Research Lab

David AI is an audio data research company. We build audio datasets with the same rigor that researchers apply to model development. That means two things:

One, we take a research-driven approach to identifying what datasets to collect, evaluating and iterating on those datasets—not just for ‘data quality’, but also for efficacy in model training—and scaling them with extreme attention to detail.

Two, our company is focused on audio. This enables us to invest deeply in audio products, infrastructure, operations, and models which, in turn, allows us to build the best audio datasets in the world.

What’s Next

In under a year, we’ve grown to support most of the “Mag 7” companies and nearly every leading audio AI lab. We also recently crossed eight figures in annual revenue run rate.

With this Series A, we’re growing the team. If you're excited about our mission and the hard problems we’re solving in audio, we’d love to hear from you. We’re hiring across research, product, engineering, and operations.

Apply at here or reach out directly: tomer [at] withdavid [dot] ai.