Langflow Multi-Agent Research Framework Development

A multi-agent AI framework that automates research and report writing. I designed it in Langflow with LangChain, orchestrating Claude and other large language models as coordinated agents that gather information, synthesise findings, and produce structured reports with minimal human input.

Research reporting is slow and repetitive — gathering sources, extracting what matters, and writing it up consistently. A single LLM call isn't enough; the work needs to be broken into steps and handled by specialised agents. The client wanted a reusable framework, not a one-off script, that could run this pipeline reliably.

A multi-agent architecture in Langflow, with each agent owning a stage of the research pipeline

LangChain orchestration coordinating retrieval, reasoning, and synthesis

Integration of Claude and other LLMs, routed to the right task for quality and cost

A Python backbone for custom logic, tool calls, and data handling

A reusable, configurable framework that can be pointed at new research topics

Python, LangChain, Langflow, Claude, and OpenAI.

The client got a working multi-agent system that turns a research question into a structured report automatically — replacing hours of manual gathering and writing with a coordinated pipeline of AI agents.