Salesforce has unveiled two new AI models—xGen-Sales and xLAM—designed to enhance its Agentforce platform, which integrates human and autonomous AI agents for improved business efficiency.
xGen-Sales is a proprietary AI model fine-tuned for sales-related tasks, such as generating customer insights, summarizing calls, and managing pipelines. It automates routine sales activities, allowing sales agents to focus on more strategic tasks. This model boosts Agentforce’s ability to autonomously handle customer interactions, nurture pipelines, and assist sales teams with greater speed and accuracy.
The xLAM (Large Action Model) family introduces AI models designed to execute complex tasks and trigger actions within business systems. Unlike traditional LLMs (Large Language Models), which are content-driven, xLAM models specialize in function-calling—allowing AI agents to act independently, such as initiating workflows or processing data without human intervention. The xLAM models range in size and capabilities, from smaller, on-device models to larger, more robust models for industrial applications.
Salesforce AI Research developed the xLAM models using APIGen, a proprietary data-generation pipeline that helped boost model performance. Early versions of xLAM models have already outperformed other large models on key benchmarks. For example, the xLAM-8x22B model ranked No. 1 in function-calling tasks on the Berkeley Leaderboards, surpassing even larger models like GPT-4.
These innovations are designed to empower businesses to scale AI-driven workflows more efficiently. Organizations using these models can now automate complex tasks, improve sales processes, and optimize resource allocation.
The non-commercial xLAM models are available on Hugging Face for community review, while the proprietary versions will power Agentforce. xGen-Sales has completed its pilot phase and will soon be available for general use.
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