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Who’s it for?

LMOS is designed for individuals and organizations aiming to develop individual AI agents and then evolve from individual AI agents to an integrated, multi-agent system. This includes:

  • Developers: Those who want to create individual AI agents and then seek to unify them into a cohesive system.

  • Companies: Organizations looking to connect AI agents developed by various departments to enhance collaboration.

  • Collaborative Companies: Multiple organizations working together, desiring a platform that facilitates seamless integration of their AI agents.

The following diagram illustrates the path from a single-agent system to a multi-agent system.

Multi Agents

Single-Agent System​

In a single-agent system, a single Agent is responsible for processing a Query and generating an Output. The agent might interact with multiple tools to complete its objective. The tools provide additional capabilities, but all decision-making and execution rely on a single entity. This system is simple but limited in scalability, as one agent must handle all tasks independently.

Multi-Agent System​

In a multi-agent system, the process is decentralized. For example in a hierarchical topology, a Supervisor might manage the incoming Query and delegates tasks to specialized Agents (FAQ Agent, Billing Agent, Sales Agent). Each agent focuses on a specific function, allowing for more efficient and scalable processing. The results from these agents are then compiled into an Output. This structure improves task specialization, parallel processing, and flexibility in handling diverse queries.

Example Scenario​

Consider a company that initially created a customer service chatbot to handle basic inquiries. As the company grows, it develops specialized AI agents to handle different areas of customer interaction, such as frequently asked questions, billing inquiries, order-related issues, sales offers, technical support, and general knowledge queries. While these agents are developed independently to focus on their specific tasks, they need to work together seamlessly to ensure a smooth and efficient customer experience. With LMOS, all these agents, whether created by different teams in different languages or even different companies, can be integrated into a single unified system. They can share data, collaborate on tasks, and communicate with each other, making the entire system more efficient, flexible, and scalable.

Summary​

LMOS makes it possible to connect diverse web-based agents, allowing organizations to manage them together as a single unit, regardless of the tools, frameworks, or languages used to build each one. Whether you're working on a small-scale project or a large enterprise-level deployment, LMOS helps you build a connected, interoperable network of intelligent agents that can grow and evolve alongside your needs.