A new arXiv preprint describes a sales agent named Javo, fine-tuned on 4.6 million consented and de-identified commercial conversations. The study aims to determine whether such a specialized agent can outperform both a frontier general-purpose model and human sales associates.
The evaluation includes both benchmark testing and randomized field evidence, according to the abstract. The abstract does not report results, only the design of the test. It notes that the evaluation has four components, but the excerpt cuts off before listing them.
The study's significance lies in its use of real-world commercial conversations for fine-tuning and its combination of controlled benchmarks with field randomization. However, without the full paper, the outcome remains unknown.