AI-Research Assistant

AI-Research Assistant is built around a multi-agent workflow that separates discovery, content extraction, and synthesis into focused responsibilities. This structure makes the research pipeline easier to reason about and extend.

The research agent uses Tavily Search API to identify relevant sources, while the extraction layer processes web content before it is passed into the summarization workflow. LangChain coordinates the orchestration between agents and model calls.

A Llama 3.1 model generates structured summaries from the collected material, helping users move from scattered search results to concise technical insight.