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Koa , 9.15日 Salesforce 推出了基于 Nvidia Nemotron 3模型训练的 CRM 大模型

Koa , 9.15日 Salesforce 推出了基于 Nvidia Nemotron 3模型训练的 CRM 大模型 Purpose-built modelsKoa 基于近三十年的 CRM 部署经验构建通过对 NVIDIA Nemotron 开源模型进行后训练并采用专有的合成数据集——该数据集模拟了企业实际运营方式涵盖其流程、工作流和运营策略。在与 NVIDIA 的深度技术合作下Koa 专为在目标企业任务上提供更深层次的专业能力而设计。Fine-tuned for complex CRM workKoa 的训练语料完全由合成场景构建这些场景模拟了 Agentforce 智能体在客户全生命周期中所执行的推理、工具调用和决策过程——从线索生成到服务工单解决——覆盖制造、金融服务、医疗保健和旅游等 14 个以上行业。每个场景都将特定角色与具体任务配对并映射出完成任务所需的确切行动序列。Kept inside the trust boundaryNVIDIA Nemotron 的开源模型让 Salesforce 能够将 CRM 智能直接构建到模型本身。Salesforce 掌控模型权重并完全在其自有基础设施内运行 Koa——因此在训练或推理过程中任何客户数据都不会跨越信任边界。最终成果一个专为驱动您的 Agentforce 用例而构建的、由 Salesforce 托管的专业化模型。Better outputs outcomesSalesforce 是 Koa 的首个客户customer zero在各类 CRM 用例中对其进行测试和基准评估例如帮助智能体、员工智能体、活动智能体、网页智能体等。Koa 的性能通过 Salesforce 的 CRM Bench 来衡量该基准基于真实业务任务构建例如更新商机、流转工单以及安排后续跟进。Purpose-built modelsKoa is grounded in nearly three decades of CRM deployments, built by post-training NVIDIA Nemotron open models with a proprietary synthetic dataset modeled on how businesses actually run: their processes, workflows, and operational policies. Developed through deep technical collaboration with NVIDIA, its purpose-built to deliver deeper expertise on targeted enterprise tasks.Fine-tuned for complex CRM workKoa’s training corpus is built entirely from synthetic scenarios simulating the reasoning, tool use, and decision-making Agentforce agents perform across the customer lifecycle — from generating leads to resolving service cases — spanning 14 industries like manufacturing, financial services, healthcare, and travel. Each scenario paired a persona with specific tasks and mapped the exact sequence of actions needed to complete them.Kept inside the trust boundaryNVIDIA Nemotrons open models gave Salesforce the control to build CRM intelligence directly into the model itself. Salesforce controls the weights and runs Koa entirely within its own infrastructure — so no customer data ever crosses the trust boundary during training or inference. The result: a specialized, Salesforce-hosted model purpose-built to power your Agentforce use cases.Better outputs outcomesSalesforce is customer zero, using Koa to test and benchmark across a variety of CRM use cases, such as help agents, employee agents, event agents, web agents, and more. Koas performance is measured on Salesforces CRM Bench, a benchmark built from real-world tasks like updating an opportunity, routing a case, and scheduling a follow-up.https://www.salesforce.com/agentforce/koa/模型是基于数据的没有独特的数据模型是不会具备特定能力的。https://www.salesforce.com/news/press-releases/2026/09/15/koa-reasoning-model/SAN FRANCISCO, September 15, 2026 — Salesforce and NVIDIAtoday announced Koa, Salesforce’s first CRM reasoning model for Agentforce, built on NVIDIA Nemotron. Developed through deep technical collaboration with NVIDIA, Koa is purpose-built to help agents reason through complex, multistep workflows and use the right tools to get work done.Koa was built by post-training NVIDIA Nemotron 3 Super with a proprietary synthetic dataset modeled on enterprise knowledge from nearly three decades of CRM deployments. The result is a reasoning model grounded in how businesses run — their processes, workflows, and operational policies. In Salesforce’s CRM benchmark, a model benchmark that includes a suite of real-world tasks like updating an opportunity, routing a case, or scheduling a follow-up, Koa already matches or exceeds leading model performance on CRM actions with three times fewer errors. Salesforce controls the model weights and performs post-training and inference entirely within its own trust boundary, giving customers a specialized, Salesforce-hosted option to power their Agentforce use cases.Salesforce and NVIDIA are also bringing Nemotron-based models and accelerated computing into Missionforce, extending that same control over model, data, and deployment environment to government and regulated organizations. Together, the companies are bringing mission-specific AI to private clouds, air-gapped networks, and other secure environments.“The most valuable thing Salesforce has built isn’t our platform — it’s the accumulated knowledge of how enterprise business actually works. With Koa, the knowledge is put inside the model itself. We trained a reasoning engine that understands the structure of a deal, the lifecycle of a service case, and the workflows that vary across industries. That’s a different kind of intelligence, and it runs entirely inside your trust boundary.”— Marc Benioff, Chair and CEO, Salesforce“AI is creating a much larger opportunity for software. Every company needs useful AI, tailored to its knowledge, expertise, and work. NVIDIA Nemotron open models give Salesforce the foundation to turn decades of enterprise expertise into specialized AI with Koa, creating a CRM model that can reason and securely take action.”— Jensen Huang, founder and CEO of NVIDIAWhat makes Koa differentNo customer data was used to train the Koa reasoning model. Its training corpus was built entirely from synthetic scenarios that reflect the reasoning, tool use, and decision-making skills Agentforce agents perform across CRM workflows: generating leads, qualifying opportunities, and resolving service cases across the customer lifecycle.Rather than relying on generic content, these scenarios were built to simulate real-world enterprise workflows across more than 14 industries, including manufacturing, financial services, healthcare, and travel. Each scenario paired a persona with specific tasks then mapped the sequence of actions and tool calls an agent must take to complete them.To post-train the model, Salesforce applied Supervised Fine-Tuning (SFT) and reinforcement learning with Group Relative Policy Optimization (GRPO) with NVIDIA NeMo RL, NeMo Gym, and NeMo AutoModel. By training on a targeted set of prioritized enterprise tasks, the model developed deeper expertise and learned not only to produce the right answer but to take the right action, step by step, to reach a goal.NVIDIA Nemotron open models gave Salesforce the control to build CRM intelligence into the model itself. Salesforce controls the weights and runs Koa within its own infrastructure, ensuring that no customer data crosses the trust boundary during inference.Koa is already in use inside Salesforce, including an agent in Slack that helps employees find information and complete everyday tasks in Slack, and is now moving into customer pilots with 1-800Accountant, Baxter Credit Union (BCU), Engine, Formula 1, UChicago Medicine, and Xero.“Accounting requires navigating tax rules, financial data, documents, and the unique circumstances of every customer. Koa gives our agents the reasoning to work through that complexity step by step and use the right tools along the way. That means we can extend more of our accountants’ expertise across every customer interaction and help people get to the right outcome faster.”— Ryan Teeples, Chief Strategy Officer, 1-800Accountant“Our members come to us with goals, whether that’s buying a home, managing their money, or planning for what’s next. Koa can help our Digital agents understand the full complexity and context behind those goals and reason across the information, tools, and policies needed to move them forward. It gives us a powerful way to make every interaction more intelligent, personal, and useful.”— John Sahagian, SVP and Chief Data Officer, Baxter Credit Union“At Engine, we’re building the future of business travel, and that starts with equipping our teams to deliver exceptional service. Business travel has countless moving parts, and what we need from AI isn’t a model that sounds confident — it’s one that can reason precisely through complex, multi-step problems. Collaborating with Salesforce and NVIDIA on a reasoning model purpose-built for Agentforce lets us push that vision further, faster.”— Elia Wallen, Founder and CEO, Engine“Some of the most important work in healthcare happens behind the scenes, coordinating information, navigating complex processes, and making sure the right next step happens at the right time. Koa can work across those longer, multi-step workflows and help our teams manage that complexity more effectively. That creates more time and capacity for what matters most, caring for patients.”— Andrew Chang, Chief Marketing Officer, UChicago Medicine---
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