Argot is a translation engine powered by reinforcement learning. It doesn't just translate the languages Google and DeepL already handle. It learns the ones they've never tried.
Of the 7,000+ languages spoken today, existing translation tools serve roughly 30 well. Another 100 poorly. The rest? Invisible. Billions of people communicate in languages that AI has never been trained on. Medical workers can't understand patients. Aid workers can't read reports. Communities can't access the internet in their own tongue.
Submit text in any language. Argot routes through specialized models optimized per language pair, not one-size-fits-all neural translation.
Native speakers flag errors and suggest improvements. A reinforcement learning loop trains the model to prefer translations that real humans approve.
Every correction makes every future translation better. Languages with less data improve faster because each signal carries more weight.
Argot combines reinforcement learning research with production-grade translation infrastructure. Built by an ML researcher who proved that LLMs can outperform traditional NMT on low-resource languages. This isn't a side project. It's the future of how 3 billion underserved people will access the internet.