Salesforce has introduced a generative AI system designed to prioritize data privacy through a unique “forgetting” feature. This innovation allows the AI to process information through large language models (LLMs) without retaining the data, helping companies manage sensitive information more securely.

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As part of the latest wave in generative AI, Salesforce’s solution takes the form of digital “agents”—intelligent systems capable of understanding and responding to customer inquiries autonomously. CEO Marc Benioff has hailed this development as a significant breakthrough for the company, emphasizing its potential to transform customer interactions.

At a recent event, Patrick Stokes, Salesforce’s EVP of Products and Industries, highlighted how this system supports organizations by reducing the costs and risks associated with building their own AI models. According to Stokes, many companies lack the resources to develop in-house AI sustainably, and Salesforce’s privacy-first approach provides an appealing alternative. Rather than focusing solely on creating the most powerful LLM, Salesforce has built AI agents that connect data and actions securely, addressing privacy concerns that have hindered AI adoption.

Salesforce’s approach integrates privacy-focused safeguards, which Stokes describes as a “trust layer” within the AI system. This feature verifies that data retrieved during an AI query aligns with the user’s access permissions, protecting sensitive information. Stokes notes that unlike traditional AI models that retain data, Salesforce’s LLM processes only the information required for each interaction and then “forgets” it afterward. This zero-retention approach creates a more secure environment, where companies retain governance over data usage and minimize risks associated with long-term data storage.

Zahra Bahrololoumi, CEO of Salesforce UK and Ireland, also emphasized that Salesforce’s AI solutions offer users the confidence to adopt generative AI without compromising security. With over 1,000 AI agents already implemented, companies are benefiting from reduced burnout and increased productivity while maintaining data trust and integrity.

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