deep-research

To automate a literature review with multi-source citations, you provide a topic and scope to trigger a tree-like exploration. The system decomposes the question into focused subtopics, orchestrates five parallel research streams, and aggregates the findings into a structured, citation-rich report.

The best way to conduct structured market analysis across multiple sources is using a parallel research architecture. This approach orchestrates five simultaneous focus areas to accelerate discovery, performing cross-source comparisons and aggregating results with credible citations into an organized report.

Yes, you can use this for technology evaluation requiring credible sources. The system is specifically designed to automate rigorous synthesis on complex topics, orchestrating parallel subagents to explore subtopics and producing structured outputs with key findings and citations.

Tree-like exploration for synthesizing complex research topics works by decomposing broad questions into focused subtopics. It then orchestrates parallel subagents to investigate these areas simultaneously, aggregating the multi-source data with structured citations into a final comprehensive report.

A limitation of using parallel subagents for deep research is the reliance on five fixed simultaneous focus areas to accelerate discovery. Users must provide a clear topic and scope upfront, as the structured output depends entirely on this initial decomposition rather than interactive, ad-hoc querying.