The Sequence Engineering #661: Create Your Own Deep Research Agent with DeerFlow
The frameworks allows the creation of end-to-end research workflows.
DeerFlow (Deep Exploration and Efficient Research Flow) is an open-source multi-agent research automation framework developed by ByteDance and released under the MIT license in 2025. Designed to address the increasing demand for scalable, auditable, and extensible research workflows, DeerFlow goes beyond the conventional single-agent LLM wrappers. It implements a graph-based orchestration of specialized agents that automate research pipelines end-to-end. Whether the task involves web search, data analysis, report generation, or podcast creation, DeerFlow delivers structured and multimodal outputs with minimal human intervention. This essay explores DeerFlow's architectural underpinnings, key capabilities, and use cases, offering a technical perspective ideal for AI developers, research engineers, and MLOps practitioners.