Browsing: multiagent

Enterprises are managing ever-growing volumes of content, ranging from product catalogs and support articles to knowledge bases and technical documentation. Ensuring this information remains accurate, relevant,…

@tool def sql_investigate(query: str) -> dict: try: df = con.execute(query).df() head = df.head(30) return { “rows”: int(len(df)), “columns”: list(df.columns), “preview”: head.to_dict(orient=”records”) } except Exception as e:…

Modern AI applications rely on intelligent agents that think, cooperate, and execute complex workflows, while single-agent systems struggle with scalability, coordination, and long-term context. AgentScope AI…

Multi-agent solutions, in which networks of agents collaborate, coordinate, and reason together, are changing how we approach real-world challenges. Enterprises manage environments with multiple data sources,…

Our work with large enterprise customers and Amazon teams has revealed that high stakes use cases continue to benefit significantly from advanced large language model (LLM)…

AI Agents are being widely adopted across industries, but how many agents are needed for an Agentic AI system? The answer can be 1 or more.…

In this tutorial, we build an advanced multi-agent incident response system using AgentScope. We orchestrate multiple ReAct agents, each with a clearly defined role such as…

In this tutorial, we build an advanced yet practical multi-agent system using OpenAI Swarm that runs in Colab. We demonstrate how we can orchestrate specialized agents,…

In this tutorial, we build an advanced, end-to-end multi-agent research workflow using the CAMEL framework. We design a coordinated society of agents, Planner, Researcher, Writer, Critic,…

In this tutorial, we build an advanced, fully autonomous logistics simulation in which multiple smart delivery trucks operate within a dynamic city-wide road network. We design…