TechCrunch AIDoubao · 实盘不做把握 6/10不做原因:标的无直接敞口
北京时间·🕒 发布 20:00:00(美西 05:00)·⟳ 抓取 20:00:48 +48s·⚡ 决策 09-15 20:03:12 +2m24s·42.0 天前
Salesforce 联手英伟达在 Dreamforce 推出首款推理模型 Koa(基于 Nemotron 开源权重),主打企业级低成本替代 Claude/ChatGPT
Koa 是超大市值公司的软产品发布:无收入/订单/指引增量,底层英伟达合作 3 月已官宣,受冲击的前沿实验室未上市且被 ClaudeForce 合作对冲;无市值更小、敞口更纯的可交易二阶标的,不构成正期望短线机会
📄 原文TechCrunch AI↗ 原文
Salesforce and Nvidia’s new reasoning model is everything the AI labs should fear
A new AI model called Koa is one of the biggest announcements from Salesforce this week at its giant Dreamforce tech co…
不做 Salesforce(CRM.US)
超大市值软产品发布,无订单/收入/指引增量,Koa 停留在发布阶段且底层合作 3 月已官宣,叠加次日 FOMC 宏观风险,无短线 edge
不做 NVIDIA(NVDA.US)
Nemotron 开源权重生态合作非新增收入,对万亿级市值无 materiality,属叙事性利好
展开详情(成交明细 / 研究档案 / 原文全文 / 决策记录链)
研究档案
结论摘要
Salesforce 基于英伟达 Nemotron 推出企业推理模型 Koa,属 Dreamforce 产品叙事,没有订单、收入或指引等财务增量,底层合作 3 月已公开;对 CRM、NVDA 两大超大市值标的均无足够 materiality,竞争对手 Anthropic/OpenAI 未上市且公司同时拥抱 Claude,故不做。
消息传播链
- Salesforce 与英伟达早在 3 月即官宣基于 Nemotron 合作为受监管行业提供低成本企业 AI agent,本次 Koa 的底层合作框架并非新信息
- Dreamforce 期间发布 Koa 模型专题,时点为美东 08:00 盘前,文中无任何财务/订单/指引数据,并同步披露与 Anthropic 的 ClaudeForce 合作市场反应:发布时美股盘前未连续成交,尚未见相关标的明确价格反应
关键理由
- 发布仅证明模型能力与可用性,尚无客户采用、付费调用量或商业化数据,按产品发布分层仍停在“发布”阶段
- Salesforce×英伟达 Nemotron 合作于 2026-03-16 已官宣,Koa 是该既有合作的产品落地,新增信息有限
主要风险
- Dreamforce 期间可能另有 Agentforce 商业化数字或上调指引,若出现硬数据需重估
- 明日 FOMC 利率决议与点阵图带来宏观波动,放大软催化标的的双向噪音
反向证据
- 做多前查反向 · 来源 web · 日期 2026-09-15 · 影响 weakens
报道未给出任何客户采用、订单金额、收入分成或指引上调;同时 Salesforce 宣布 ClaudeForce,削弱“替代前沿模型”的多头叙事
检索:Salesforce Agentforce Koa revenue guidance orders Dreamforce 2026 原文 ↗
先例如何影响了这次决策
对本次决策的影响:确认 AVOID:软催化 + 旧合作新包装 + 无金额增量,不出任何腿
方向:未进入 ENTER 研判,未构建先例面板:超大市值软产品发布、无财务增量,按经验先验默认不做,先例幅度不改变 AVOID 结论
涨幅量级:无可用于校准的对齐先例,且本事件无交易级 materiality
形态:经验库同类案例(NVDA AI 工厂合作、阿里产品整合)显示超大市值软催化短线胜率与盈亏比偏差,故不参与
工具执行结果 · 成功 3 · 降级 0 · 失败 0 · 取消 0
- search_processed_events 成功 stock_tools HTTP · 23 ms
{"result": "search_processed_events:agent query=`claudeforce salesforce anthropic partnership | salesforce koa reasoning model nemotron nvidia dreamforce | salesforce nvidia koa agentforce open-weight model announcement`;结构化索引覆盖完整 72 小时;旧记录兼容扫描近 0.0/72 小时、0 条本臂决策(完整),返回 0 条候选。未命中只表示这些 agent query 表达 - fetch_decision_experience 成功 stock_tools HTTP · 46 ms
{ - web_search 成功 doubao_search · 2,239 ms
豆包搜索结果(原始查询:Salesforce Koa reasoning model Nvidia Nemotron Agentforce announcement;API SearchType:web)
原文全文
展开原文 · 3,821 字
A new AI model called Koa is one of the biggest announcements from Salesforce this week at its giant Dreamforce tech conference. Koa is the company’s first reasoning model, built on Nvidia’s open-weight Nemotron model. The two companies worked together to post-train Koa to excel at sales, marketing, and customer-support-related tasks.
Koa is a shining example of how the enterprise world’s needs for AI are diverging from what the frontier labs are offering. Proprietary AI labs would rather have enterprises uploading files, code, prompts, and feedback directly into their models and agents, and spending millions to do so.
But with the model, Salesforce is offering its enterprise customers:
- an open-weight alternative to closed frontier models
- a model trained to do specific work tasks (rather than to solve impossible math problems)
- one that has not ingested any actual customer data and therefore cannot leak it to others
- a model that helps reduce AI spending, since it uses fewer tokens to do the same work
- one that can be automatically routed through an AI “gateway,” depending on the need
- and a model that follows all of a customer’s data requirements and security embedded within Salesforce.
Koa will be provided as an alternative to the other models Salesforce offers in its Agentforce platform, where its customers build agents to handle rote tasks like answering customer service questions or scheduling appointments.
“We’ve built many small task-specific language models, which are part of Agentforce’s portfolio,” Jayesh Govindarajan, EVP of Salesforce AI, told TechCrunch. “But reasoning has always been something that we’ve relied on the frontier model providers for. Until now.”
Before Koa, if an agent needed to reason through a long-running or multi-step task, those prompts would be routed to a frontier model like Claude or ChatGPT through Agentforce’s AI gateway (the system that decides which model handles which request).
“One of the reasons we hadn’t done this before, train our own enterprise-grade frontier model — we always wanted to — but the challenge has always been the lack of a pre-trained base model to start with. Until Nemotron came along, there was no sovereign American pre-trained model that was available, one, and two, that was state of the art, and, three, that had clear data provenance. We have no idea what Qwen trains on,” Govindarajan said, referring to the popular Chinese open-weight model produced by Alibaba.
Post-training a model like this means taking it from a general-purpose system to one well-versed in sales and customer support knowledge, and to do that, Salesforce and Nvidia did not use any actual data from Salesforce’s customers. Instead, they crafted synthetic data that mimicked customers’ patterns.
“We actually simulated a customer service environment with a persona customer service professional, including irate customers that call into the customer service center, all the way to a sales professional who’s trying to close a deal,” Govindarajan described.
Koa is meant to be better at the work tasks Salesforce customers want an agent to do — and cheaper, in terms of tokens burned — than sending those same tasks to Claude or ChatGPT.
With Nemotron, “we have a unique architecture for inference to be token efficient,” Kari Ann Briski, Nvidia’s VP of Generative AI Software for Enterprise, told TechCrunch. “It’s kind of the trifecta of things that you need to have: sovereign AI, time to first token, efficient reasoning, for the tokenomics of it all.”
However, Salesforce isn’t exactly abandoning Anthropic or OpenAI. It just announced a partnership with Anthropic called ClaudeForce that allows companies to use Claude as their AI interface, while their data remains in Salesforce’s system of records, secured by its infrastructure.
Koa is a shining example of how the enterprise world’s needs for AI are diverging from what the frontier labs are offering. Proprietary AI labs would rather have enterprises uploading files, code, prompts, and feedback directly into their models and agents, and spending millions to do so.
But with the model, Salesforce is offering its enterprise customers:
- an open-weight alternative to closed frontier models
- a model trained to do specific work tasks (rather than to solve impossible math problems)
- one that has not ingested any actual customer data and therefore cannot leak it to others
- a model that helps reduce AI spending, since it uses fewer tokens to do the same work
- one that can be automatically routed through an AI “gateway,” depending on the need
- and a model that follows all of a customer’s data requirements and security embedded within Salesforce.
Koa will be provided as an alternative to the other models Salesforce offers in its Agentforce platform, where its customers build agents to handle rote tasks like answering customer service questions or scheduling appointments.
“We’ve built many small task-specific language models, which are part of Agentforce’s portfolio,” Jayesh Govindarajan, EVP of Salesforce AI, told TechCrunch. “But reasoning has always been something that we’ve relied on the frontier model providers for. Until now.”
Before Koa, if an agent needed to reason through a long-running or multi-step task, those prompts would be routed to a frontier model like Claude or ChatGPT through Agentforce’s AI gateway (the system that decides which model handles which request).
“One of the reasons we hadn’t done this before, train our own enterprise-grade frontier model — we always wanted to — but the challenge has always been the lack of a pre-trained base model to start with. Until Nemotron came along, there was no sovereign American pre-trained model that was available, one, and two, that was state of the art, and, three, that had clear data provenance. We have no idea what Qwen trains on,” Govindarajan said, referring to the popular Chinese open-weight model produced by Alibaba.
Post-training a model like this means taking it from a general-purpose system to one well-versed in sales and customer support knowledge, and to do that, Salesforce and Nvidia did not use any actual data from Salesforce’s customers. Instead, they crafted synthetic data that mimicked customers’ patterns.
“We actually simulated a customer service environment with a persona customer service professional, including irate customers that call into the customer service center, all the way to a sales professional who’s trying to close a deal,” Govindarajan described.
Koa is meant to be better at the work tasks Salesforce customers want an agent to do — and cheaper, in terms of tokens burned — than sending those same tasks to Claude or ChatGPT.
With Nemotron, “we have a unique architecture for inference to be token efficient,” Kari Ann Briski, Nvidia’s VP of Generative AI Software for Enterprise, told TechCrunch. “It’s kind of the trifecta of things that you need to have: sovereign AI, time to first token, efficient reasoning, for the tokenomics of it all.”
However, Salesforce isn’t exactly abandoning Anthropic or OpenAI. It just announced a partnership with Anthropic called ClaudeForce that allows companies to use Claude as their AI interface, while their data remains in Salesforce’s system of records, secured by its infrastructure.
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