Agentflow vs AutoGen

Agentflow is an AI agent orchestration platform designed to help developers and businesses create, deploy, and manage autonomous AI workflows with minimal complexity.

It provides a visual, drag-and-drop interface for building agent pipelines, allowing users to connect large language models, APIs, and business tools without heavy coding.

Agentflow emphasizes simplicity and scalability, making it accessible for non-technical teams while still powerful enough for developers.

Its framework supports task delegation, multi-step reasoning, and tool integration, enabling AI agents to perform complex actions such as research, report generation, or workflow automation.

AutoGen is an open-source framework developed by Microsoft for building multi-agent AI systems and advanced LLM-powered applications.

It enables developers to create autonomous agents that can collaborate, converse, and solve problems together, or with human feedback integrated into the loop.

AutoGen provides abstractions for defining roles, tasks, and communication protocols between agents, allowing flexible setups from simple assistants to complex, multi-agent ecosystems.

It is designed for rapid prototyping as well as production deployment, with features like conversation orchestration, human-AI collaboration, and tool integration.