Koa puts decades of Salesforce’s CRM knowledge into a reasoning model built to handle the operational work behind customer interactions.
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Salesforce hopes its new tailored-for-CRM AI will be a boon for marketers and a moat against the general-purpose models of companies like OpenAI, Anthropic, and Google.
At Dreamforce, the company introduced Koa, its first CRM reasoning model, developed with Nvidia to work through complex, multistep sales, service, and customer workflows. Instead of simply answering questions or generating content, Koa is designed to determine which tools and actions are needed to complete a job.
For marketers, that distinction matters as AI agents take on more operational work. Writing an email is relatively straightforward. Deciding whether a lead qualifies, checking its account history, applying company rules, updating the CRM, and triggering the appropriate sales or nurture workflow requires the model to understand how the business operates.
Koa is Salesforce’s attempt to put some of that operational knowledge directly into the model.
“The most valuable thing Salesforce has built isn’t our platform — it’s the accumulated knowledge of how enterprise business actually works,” Marc Benioff, Salesforce’s chair and CEO, said in a statement. “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.”
Koa learns how CRM work gets done
Salesforce built Koa on Nvidia’s Nemotron 3 Super and post-trained it using a proprietary synthetic dataset modeled on the company’s decades of experience with CRM deployments. No customer data was used to train the model.
Its training scenarios cover more than 14 industries and recreate workflows such as generating leads, qualifying opportunities, and resolving service cases. Each scenario maps the actions and tool calls needed to complete a task, teaching Koa to work through the steps required to reach an outcome rather than simply produce an answer.
Salesforce also controls the model weights and performs inference within its own infrastructure, so customer data doesn’t cross its trust boundary when Koa is being used. That’s particularly relevant when an agent moves beyond generating marketing assets and starts accessing customer information, changing records, or triggering workflows.
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The company says it is “moving into customer pilots” with 1-800Accountant, Baxter Credit Union, Engine, Formula 1, UChicago Medicine, and Xero. General availability in U.S. regions is expected this winter.
Marketers may need more than one AI model
Koa isn’t replacing the general-purpose models Salesforce customers already use. Salesforce is expanding those choices at the same time it develops its own specialized model.
Agentforce customers can use Gemini models through Salesforce’s Google Cloud partnership. An expanded AWS integration adds models available through Amazon Bedrock, including models from Anthropic, Nvidia, and OpenAI.
That points toward a different way of thinking about AI in the martech stack. Instead of choosing a single model to handle everything, companies could use different models for different tasks.
A general-purpose model might be a good choice for brainstorming a campaign, analyzing research, or drafting content. A specialized model such as Koa could handle jobs that require knowledge of CRM processes, company rules, customer records, and the sequence of actions needed to complete a workflow.
For marketing operations teams, model selection could become another orchestration decision. Cost, accuracy, speed, access to customer data, governance requirements, and the consequences of an error could determine which model gets a particular job.
AIforce gives those models somewhere to work
Koa also fills in another piece of a Salesforce strategy already underway.
Last month, the company’s Claudeforce partnership made Salesforce’s interface optional by putting its data, business logic, and actions inside Claude. AIforce, formally unveiled at Dreamforce, expands that approach across more AI interfaces.
AIforce makes Salesforce data, workflows, semantics, permissions, security, governance, and actions available
The company’s expanded partnerships with AWS and Google Cloud further extend that architecture. Salesforce capabilities can surface inside Amazon Quick and Gemini Enterprise, while models and agents from those ecosystems can operate with Salesforce data and workflows.
For marketers, the interface where work happens and the technology doing the work are becoming separate choices. Salesforce can provide customer context and business rules, Claude or Gemini can provide general-purpose reasoning, and Koa can handle work where specialized CRM knowledge is more useful.
The same shift is reaching customers
Salesforce’s expanded Google partnership shows what this separation can look like on the customer side.
Starting this fall, Commerce Cloud merchants will be able to surface products in Google Search, including AI Mode and Gemini. Customers can complete purchases through Google’s Universal Commerce Protocol while payments, compliance, and order management remain on the merchant’s Commerce Cloud infrastructure.
The customer can interact with Google while Salesforce operates underneath the experience.
That’s a significant change for marketers accustomed to thinking about customer journeys in terms of websites, apps, ecommerce stores, and other brand-controlled destinations. As AI interfaces become another place where discovery and transactions happen, the technology determining what customers see and what happens next is largely invisible to them.
Similarly, marketers may do less directly with the applications in their stack as agents handle more of the navigation between them.
That puts more weight on what’s underneath the interface: accurate customer data, consistent definitions, permissions, business rules, APIs, and governance. It also places greater emphasis on choosing the right reasoning for the job.
In a world where AI makes information cheap and expertise easier to access, Salesforce is betting that experience is harder to copy.
MarTech is owned by Semrush. We remain committed to providing high-quality coverage of marketing topics. Unless otherwise noted, this page’s content was written by either an employee or a paid contractor of Semrush Inc.
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