Rohan Paul

A cascaded voice agent just won a blind human-preference ranking against native speech-to-speech models. Today, Cartesia launched Managed Agents, ranked #1 on Artificial Analysis’ Speech Agent Arena. Most LLMs learn from chunks of text picked by a tokenizer. But here, H-Nets learn directly from raw bytes and figure out those boundaries themselves. This leads to 3–5x better efficiency in controlled scaling experiments. At larger scale, matching an open-source model trained on 11 trillion tokens with roughly 10x less training data and compute. > #1 in blind human preference and #1 in enterprise accuracy > Cascaded stack that sounds as natural as speech-to-speech > Own speech models and agent harness tuned as one system