Banger report from Salesforce. Pretty interesting to see more of these custom enterprise models. Salesforce trained the enterprise agent model from the same files it uses to configure agents. Koa starts from the open-weight Nemotron-3-Super-120B. Salesforce takes Agent Script specifications, the declarative files that define Agentforce agents, and expands them into multi-turn tasks with simulated user personas. The reward checks whether the agent resolved the task with the right tool calls, and training uses GRPO. The gains are modest and consistent. Koa scores 69.41 on Tau2Bench against 68.64 for its base and 54.48 for GPT-4.1. On CRM Bench it reaches 0.86, close to Claude Opus 4.8 at 0.87, and function-call accuracy rises from 0.71 to 0.77. If your company already describes its workflows in a structured format, those descriptions might be useful to turn into RL environments. Paper: Chat with Paper: