Models that teach.
Learning that sticks.

Building audio models and personalized learning experiences from petabytes of data.

The problem

Teaching starts with understanding.

Today's AI models weren't built for children learning English. In our tests, off-the-shelf models reached word error rates as high as 60% for younger learners. They struggle to identify pronunciation mistakes, segment individual phonemes, and adapt to each student's level. Prompting and fine-tuning alone haven't solved these problems. We've tried.

Our approach

So we're building better models.

We're a small research lab training next-generation audio models on millions of hours of proprietary English-learning data. Starting with spoken English for kids, we're building on open-source foundations to create AI that can truly understand, teach, and adapt to every learner.

Our first prototypes are already working, and they're getting better fast.