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October 29, 2026
At Dreamforce 2026, Salesforce AI Research’s Chief Scientists sat down with Dr. Uri Yerushalmi, Co-Founder and Chief AI Officer of Fetcherr, to discuss the difference between what separates agentic AI from something that demos to agentic AI that actually makes an impact on enterprises.
Throughout their 30-minute conversation, there were four key areas of discussion. The two went into detail about ambient intelligence, going beyond LLMs to large market models, how trust and guardrails can be incorporated into AI, and what multi-agent orchestration means across enterprises.
They started the discussion on ambient intelligence, something Yerushalmi believes resembles what creatures do in nature. He then went on to talk about how Fetcherr has built the proactive version of that intelligence, an AI that runs millions of simulations using real data to weigh up the outcomes of actions before committing to a single thing.
Fetcherr's modeling approach is what took the conversation beyond LLMs. Yerushalmi mentioned that LLMs are great for talking about price. The main issue is that it cannot predict the consequences of changing it. That gap is closed using Fetcherr’s Market Model, a model built on an enterprise's real transaction, demand, and inventory data.
Halfway through the conversation, the topic of trust appeared. Yerushlmi describes how Fetcherr’s Market Model is built to earn it. Each deployment starts with a narrow action space, where the model has to provide results against a control group with A/B testing. As the evidence compounds, humans can start lifting the guardrails at their own pace, letting them create the rules while the AI handles the volume.
The same principles carry into multi-agent ecosystems, where centralized Market Models advise agents negotiating inside and across enterprises. This keeps everything within the guardrails the business has set.
To understand more, watch the full conversation below and see how Salesforce and Fetcherr are turning an agentic promise into operational excellence.
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