deep-research

Automating long-horizon research involves decomposing broad topics into sub-questions and iteratively exploring multiple sources like papers, blogs, and code. This process structures findings into a persistent knowledge base and synthesizes a final report autonomously.

Gap analysis in autonomous research workflows is an iterative process that identifies missing information during source exploration. It continuously drives the research loop to explore new sources until all sub-questions are thoroughly investigated and synthesized into the knowledge base.

Recovering an interrupted research workflow requires using file-based checkpoints and a persistent memory workspace. This crash-resilient mechanism saves execution progress periodically, allowing you to resume the hours-long investigation from the last saved state.

You can run unattended multi-source investigations by providing only the initial topic. The structured research loop enforces autonomous decomposition, exploration, and synthesis without requiring any additional code from the user throughout the hours-long workflow.

Automated research works with papers, blogs, and code repositories through parallel exploration and multi-source synthesis. It automatically decomposes topics and structures findings from these diverse sources into a unified knowledge base for final report generation.