o9 Introduces Generative AI Agents to Digital Brain

 o9, a leading enterprise AI software platform provider for transforming planning and decision-making, today announced that it has enhanced its Digital Brain platform by incorporating generative AI-powered Large Language Model (LLM) composite agents. These next-generation agents are designed to revolutionize the way planners execute complex tasks, driving continued improvement in integrated business planning capabilities. 

o9’s composite agents are built on a foundation of atomic agents, which are AI-driven systems that are capable of performing tasks, retrieving information and generating responses to queries based upon specific inputs, coupled with Large Language Model (LLM) systems that are trained in information that is specific to a business. 

Within the o9 Digital Brain platform’s core Enterprise Knowledge Graph (EKG), composite agents are able to integrate a sequence of atomic agents to perform more complicated exercises that can be used in cross-functional planning processes, such as building a forecast or post-game analysis. This is done through a sequence of retrieving and synthesizing data to arrive at an outcome, such as analyzing month-to-month forecast changes or providing a post-game analysis of the previous quarter to compare a prior forecast to actual results and perform root-cause analysis on forecast inaccuracies. Additionally, composite agents are trained on the ‘recipes’ followed by an organization's planning experts and are able to continuously learn from feedback. This results in agents getting better at arriving at the desired outcome. 

“Our Digital Brain’s EKG offers cross-functionality as it touches supply chain, finance, procurement, commercial, customers and suppliers. It connects the knowledge of all these entities – and is constantly accumulating new knowledge as well,” said Anand Srinivasan, o9’s Chief Strategy Officer. “Now we are deploying composite agents that can do a lot more cross-functional analysis.”

Srinivasan continued, “Typically, an employee within a particular function only has the purview of knowledge, people, and systems within their department; they don’t look across and consider, ‘How does my decision impact someone else in a different department or organization?’ Hence, a lot of things get missed, and there is a lot of value leakage. This is another thing these composite agents can help solve by becoming more cross-functional in their analysis.”