In 2025, the spotlight is on AI agents that automate tasks using generative AI. A new player, Orby, has introduced the Large Action Model (LAM) to streamline enterprise operations. Unlike traditional models that focus on text, LAMs process actions like screenshots and user interactions to automate workflows in software like Salesforce and SAP. Orby’s foundation model, ActIO, collects sequence data (or “traces”) to enhance automation. Co-founder Will Lu emphasizes aligning AI solutions to real business needs, advising CIOs to identify tedious tasks that AI can simplify. With a focus on human oversight, Orby aims to improve efficiency without sacrificing security, providing a new way for enterprises to leverage technology.
In 2025, AI agents are leading innovation in the tech world, especially in enterprise settings. One of the latest players in this space is Orby, which introduces a Large Action Model (LAM) designed to streamline business operations. As companies seek to leverage generative AI, understanding how models like LAM differ from traditional Large Language Models (LLMs) is crucial.
Orby’s co-founder Will Lu defines LAMs as specialized AI models that focus on automating tasks specific to businesses. Unlike LLMs that generate text or images, LAMs process various inputs such as application screenshots and user interactions to automate complex workflows. By utilizing LAM, companies can enhance productivity and minimize time-consuming tasks.
The technology behind Orby’s LAM is called ActIO, which has collected over a million “traces” of enterprise workflow data. Each trace outlines a sequence of actions needed to complete specific tasks, informing the model of efficient practices. This capability enables enterprises to automate features present in popular software like Salesforce and SAP, thus simplifying operations.
Orby’s LAM stands apart from OpenAI’s Operator due to its focus on “grounding,” a concept integral to functioning in complex software environments. This involves identifying the essential actions required to manage tasks. Lu emphasizes that Orby’s software can operate existing applications as if a human were managing them, eliminating the need for API integrations.
For CIOs and IT leaders, Lu advises focusing on tangible business challenges where automation can play a crucial role. Simple yet labor-intensive tasks, like auditing expense reports, are perfect candidates for automation, allowing human employees to focus on more strategic initiatives.
In summary, Orby’s Large Action Model represents a forward-thinking approach to workflow automation in enterprises. With a clear focus on task-oriented actions and refined automation capabilities, it stands to reshape how businesses interact with technology.
Primary Keyword: AI agents
Secondary Keywords: Large Action Model, enterprise automation, workflow automation
What are AI agents in the workplace?
AI agents are computer programs that can perform tasks that normally require human intelligence. They help automate routine work, analyze data, and even assist in making decisions.
How can AI agents improve business efficiency?
AI agents can speed up processes by handling repetitive tasks quickly. They reduce human error and free up employees to focus on more important work, boosting overall productivity.
Are AI agents easy to use?
Yes, AI agents are designed to be user-friendly. Many come with simple interfaces and don’t require advanced technical skills. Businesses can often implement them with minimal training.
What types of tasks can AI agents automate?
AI agents can automate a wide range of tasks like scheduling meetings, managing emails, analyzing sales data, and even customer service inquiries. They can handle many tedious tasks, making work life easier.
Do AI agents replace human jobs?
AI agents can change the way we work, but they don’t necessarily replace human jobs. Instead, they assist employees, taking over repetitive tasks so that humans can focus on more creative and complex activities.
